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v1.2.2
| Author | SHA1 | Date | |
|---|---|---|---|
 Will Miao
|
6e2185c182 | ||
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Will Miao
|
41302e75ba | ||
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Will Miao
|
a17399d667 | ||
|
Will Miao
|
e2d85a0a21 | ||
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Will Miao
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303833bbae | ||
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Will Miao
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f86b7b55d6 | ||
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Will Miao
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782bb53784 | ||
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Will Miao
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139231e225 |
@@ -1,146 +0,0 @@
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---
|
||||
name: lora-manager-e2e
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description: "End-to-end testing and validation for LoRa Manager features. Use ONLY for sandboxed E2E validation of LoRa Manager standalone mode: start the standalone server on a free port with --settings-path, drive the web UI (http://127.0.0.1:{PORT}/loras) via Chrome DevTools MCP, and verify frontend-to-backend integration. NOT for UI behavior checks that unit tests (Vitest/jsdom) can cover. Trigger keywords: E2E, standalone, Chrome DevTools MCP, lora-manager-e2e, sandbox."
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---
|
||||
|
||||
# LoRa Manager E2E Testing
|
||||
|
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End-to-end testing of LoRa Manager standalone mode using Chrome DevTools MCP.
|
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|
||||
## When to Use — and When NOT To
|
||||
|
||||
E2E runs are slow and token-heavy. Reach for them only when the question genuinely
|
||||
spans server + browser (routing, scan persistence, websocket updates, EXIF writes).
|
||||
|
||||
- **Default to unit/component tests first**: `npm run test:js` (Vitest/jsdom) covers
|
||||
DOM rendering, modal behavior, event handling and API-client calls deterministically
|
||||
in seconds. Backend logic goes through `pytest`. A UI-behavior question answered by
|
||||
jsdom MUST NOT be escalated to E2E.
|
||||
- **Use E2E only when** the behavior cannot be observed without a live server and a
|
||||
real browser, e.g. template rendering through the aiohttp server, scanner → SQLite
|
||||
persistence → API → DOM round-trips, or real EXIF/image writes.
|
||||
- If you start an E2E and realize a unit test would answer the question, stop and
|
||||
switch.
|
||||
|
||||
**Browser driver is fixed: Chrome DevTools MCP.** Do not substitute kimi-webbridge —
|
||||
it operates on the user's real browser (real tabs, real sessions, synthetic
|
||||
`isTrusted=false` events), which breaks the isolation this skill requires and lacks
|
||||
the console/network inspection E2E debugging relies on. kimi-webbridge is for
|
||||
interactive browsing with the user's real login sessions, not for sandboxed E2E.
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||||
|
||||
## Conventions
|
||||
|
||||
- **`{PORT}`**: default candidate `8188`, but it is **commonly occupied by a live
|
||||
ComfyUI** — always check first (`ss -tlnp | grep ':{PORT}'`) and use a free port
|
||||
(e.g. `8199`). Substitute the chosen port everywhere below. Never kill a process
|
||||
you did not start for this E2E.
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- **`<repo-root>`**: the repository/worktree root; run all commands from there.
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- **`<sandbox>`**: a throwaway dir, e.g. `/tmp/opencode/<plan>-e2e`.
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## SANDBOX (MANDATORY)
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|
||||
> Every E2E run MUST target a throwaway sandbox, never real user data.
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|
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1. **Explicit settings directory**: always launch with `--settings-path <sandbox>/settings`.
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This pins ALL runtime data (`settings.json`, `cache/`, `backups/`, `logs/`, `stats/`,
|
||||
`wildcards/`) under the sandbox. **Never** create `<repo-root>/settings.json` — the repo
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||||
folder is usually the real ComfyUI plugin folder and a portable settings file there is
|
||||
read by the real instance.
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2. **Sandboxed library paths**: point `folder_paths` / `recipes_path` /
|
||||
`example_images_path` at disposable dirs under `<sandbox>` — never the real library,
|
||||
real recipe dir, or real settings:
|
||||
|
||||
```json
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{
|
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"folder_paths": {
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"loras": ["<sandbox>/models/loras"],
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"checkpoints": ["<sandbox>/models/checkpoints"],
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||||
"unet": ["<sandbox>/models/checkpoints"],
|
||||
"diffusers": []
|
||||
},
|
||||
"recipes_path": "<sandbox>/recipes",
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"example_images_path": "<sandbox>/example_images"
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}
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```
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|
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3. **Real-data protection proof**: before starting and after finishing, snapshot the real
|
||||
config and recipe library and confirm they are byte-identical; also confirm
|
||||
`<repo-root>` gained no `settings.json` or `cache/`:
|
||||
|
||||
```bash
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sha256sum ~/.config/ComfyUI-LoRA-Manager/settings.json > <sandbox>/settings.before.sha256
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||||
ls ~/models/recipes/*.recipe.json 2>/dev/null | wc -l > <sandbox>/recipes-count.before.txt
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||||
# AFTER the run: record again and diff. Any change = the run leaked into real data.
|
||||
```
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||||
|
||||
## Quick Start
|
||||
|
||||
```bash
|
||||
cd <repo-root>
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||||
# 1. Sandbox
|
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mkdir -p <sandbox>/settings <sandbox>/models/{loras,checkpoints} <sandbox>/{recipes,example_images}
|
||||
# write <sandbox>/settings/settings.json per the SANDBOX example
|
||||
# 2. Port
|
||||
ss -tlnp | grep ':{PORT}' || echo "port {PORT} is free"
|
||||
# 3. Server — MUST be fully detached (a plain background & dies with the shell);
|
||||
# the helper enforces this and manages its own pidfile
|
||||
python .agents/skills/lora-manager-e2e/scripts/start_server.py \
|
||||
--port {PORT} --settings-path <sandbox>/settings --wait --timeout 30 --detach
|
||||
ss -tlnp | grep ':{PORT}' # verify listening BEFORE proceeding
|
||||
# 4. Chrome with remote debugging, then connect Chrome DevTools MCP (verify via list_pages)
|
||||
google-chrome --remote-debugging-port=9222 --user-data-dir=/tmp/chrome-lora-manager http://127.0.0.1:{PORT}/loras
|
||||
```
|
||||
|
||||
Then drive the UI with the MCP tools (`take_snapshot`, `click`, `fill`, `fill_form`,
|
||||
`evaluate_script`, `wait_for`, `list_network_requests`, `list_console_messages`) —
|
||||
see [references/mcp-cheatsheet.md](references/mcp-cheatsheet.md) for patterns.
|
||||
|
||||
Server restart after config/fixture changes:
|
||||
|
||||
```bash
|
||||
python .agents/skills/lora-manager-e2e/scripts/start_server.py \
|
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--port {PORT} --settings-path <sandbox>/settings --restart --wait --detach
|
||||
# then reload the browser page (ignoreCache=True)
|
||||
```
|
||||
|
||||
`--restart` only kills the E2E server the script itself started (via its pidfile) and
|
||||
aborts instead of killing unrelated processes on the port.
|
||||
|
||||
## Abort Rule
|
||||
|
||||
A sandboxed E2E should finish in well under 30 minutes. If any phase exceeds ~2x its
|
||||
expected duration (server readiness > 60 s, MCP connect > 2 min, a single scenario >
|
||||
10 min), or any single tool call fails 3+ times in a row, **STOP** — do not retry
|
||||
blindly. Report `BLOCKED` with the phase, last observed state (server PID,
|
||||
`ss -tlnp` output, page snapshot, last API response) and suspected cause. A clean
|
||||
BLOCKED report beats an hour of retries.
|
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|
||||
## Troubleshooting
|
||||
|
||||
- **"browser is already running" / `list_pages` fails**: a stale Chrome holds the
|
||||
profile dir. Find it (`ps -ef | grep -i '[c]hrome.*user-data-dir'`), confirm it is a
|
||||
leftover QA Chrome (not the live ComfyUI, not your current MCP browser), kill only
|
||||
that PID, then retry `list_pages`.
|
||||
- **MCP refuses to write screenshots into the worktree**: save to `/tmp` via
|
||||
`take_screenshot(filePath="/tmp/...")` and copy into the evidence dir from the shell.
|
||||
|
||||
## Cleanup
|
||||
|
||||
1. Stop the standalone server: `kill <recorded-pid>` (only the PID you started), then
|
||||
confirm `ss -tlnp | grep ':{PORT}'` is empty.
|
||||
2. Close browser pages (keep at least one open).
|
||||
3. `rm -rf <sandbox>`; verify `<repo-root>` gained no `settings.json` or `cache/`.
|
||||
4. Re-run the real-data protection check from the SANDBOX section and record the result.
|
||||
|
||||
## References & Scripts
|
||||
|
||||
- [references/mcp-cheatsheet.md](references/mcp-cheatsheet.md) — Chrome DevTools MCP
|
||||
command patterns (navigation, waiting, snapshots, forms, network, console, performance).
|
||||
- [references/test-scenarios.md](references/test-scenarios.md) — detailed test scenarios
|
||||
(list display, metadata editing, recipes, settings, import/export).
|
||||
- [references/recipe-rematch-fixtures.md](references/recipe-rematch-fixtures.md) —
|
||||
fixture format, fresh-state reset and known gaps for recipe rematch/repair E2E runs.
|
||||
- `scripts/start_server.py` — start/restart the standalone server
|
||||
(`--port --settings-path --restart --wait --timeout --detach`); refuses to touch
|
||||
unrelated processes on the port.
|
||||
- `scripts/wait_for_server.py` — poll readiness (`--port --timeout`).
|
||||
@@ -1,360 +0,0 @@
|
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# Chrome DevTools MCP Cheatsheet for LoRa Manager
|
||||
|
||||
Quick reference for common MCP commands used in LoRa Manager E2E testing.
|
||||
|
||||
> **Port convention**: `{PORT}` is the port chosen for the E2E run (default candidate `8188`, but only if actually free — see the SKILL.md Port Selection section; use e.g. `8199` when `8188` is occupied by a live ComfyUI). Always run against the **sandboxed** standalone server, never a live instance.
|
||||
|
||||
## Navigation
|
||||
|
||||
```python
|
||||
# Navigate to LoRA list page
|
||||
navigate_page(type="url", url="http://127.0.0.1:{PORT}/loras")
|
||||
|
||||
# Reload page with cache clear
|
||||
navigate_page(type="reload", ignoreCache=True)
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||||
|
||||
# Go back/forward
|
||||
navigate_page(type="back")
|
||||
navigate_page(type="forward")
|
||||
```
|
||||
|
||||
## Waiting
|
||||
|
||||
```python
|
||||
# Wait for text to appear
|
||||
wait_for(text="LoRAs", timeout=10000)
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||||
|
||||
# Wait for specific element (via evaluate_script)
|
||||
evaluate_script(function="""
|
||||
() => {
|
||||
return new Promise((resolve) => {
|
||||
const check = () => {
|
||||
if (document.querySelector('.lora-card')) {
|
||||
resolve(true);
|
||||
} else {
|
||||
setTimeout(check, 100);
|
||||
}
|
||||
};
|
||||
check();
|
||||
});
|
||||
}
|
||||
""")
|
||||
```
|
||||
|
||||
## Taking Snapshots
|
||||
|
||||
```python
|
||||
# Full page snapshot
|
||||
snapshot = take_snapshot()
|
||||
|
||||
# Verbose snapshot (more details)
|
||||
snapshot = take_snapshot(verbose=True)
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||||
|
||||
# Save to file
|
||||
take_snapshot(filePath="test-snapshots/page-load.json")
|
||||
```
|
||||
|
||||
## Element Interaction
|
||||
|
||||
```python
|
||||
# Click element
|
||||
click(uid="element-uid-from-snapshot")
|
||||
|
||||
# Double click
|
||||
click(uid="element-uid", dblClick=True)
|
||||
|
||||
# Fill input
|
||||
fill(uid="search-input", value="test query")
|
||||
|
||||
# Fill multiple inputs
|
||||
fill_form(elements=[
|
||||
{"uid": "input-1", "value": "value 1"},
|
||||
{"uid": "input-2", "value": "value 2"},
|
||||
])
|
||||
|
||||
# Hover
|
||||
hover(uid="lora-card-1")
|
||||
|
||||
# Upload file
|
||||
upload_file(uid="file-input", filePath="/path/to/file.safetensors")
|
||||
```
|
||||
|
||||
## Keyboard Input
|
||||
|
||||
```python
|
||||
# Press key
|
||||
press_key(key="Enter")
|
||||
press_key(key="Escape")
|
||||
press_key(key="Tab")
|
||||
|
||||
# Keyboard shortcuts
|
||||
press_key(key="Control+A") # Select all
|
||||
press_key(key="Control+F") # Find
|
||||
```
|
||||
|
||||
## JavaScript Evaluation
|
||||
|
||||
```python
|
||||
# Simple evaluation
|
||||
result = evaluate_script(function="() => document.title")
|
||||
|
||||
# Async evaluation
|
||||
result = evaluate_script(function="""
|
||||
async () => {
|
||||
const response = await fetch('/loras/api/list');
|
||||
return await response.json();
|
||||
}
|
||||
""")
|
||||
|
||||
# Check element existence
|
||||
exists = evaluate_script(function="""
|
||||
() => document.querySelector('.lora-card') !== null
|
||||
""")
|
||||
|
||||
# Get element count
|
||||
count = evaluate_script(function="""
|
||||
() => document.querySelectorAll('.lora-card').length
|
||||
""")
|
||||
```
|
||||
|
||||
## Network Monitoring
|
||||
|
||||
```python
|
||||
# List all network requests
|
||||
requests = list_network_requests()
|
||||
|
||||
# Filter by resource type
|
||||
xhr_requests = list_network_requests(resourceTypes=["xhr", "fetch"])
|
||||
|
||||
# Get specific request details
|
||||
details = get_network_request(reqid=123)
|
||||
|
||||
# Include preserved requests from previous navigations
|
||||
all_requests = list_network_requests(includePreservedRequests=True)
|
||||
```
|
||||
|
||||
## Console Monitoring
|
||||
|
||||
```python
|
||||
# List all console messages
|
||||
messages = list_console_messages()
|
||||
|
||||
# Filter by type
|
||||
errors = list_console_messages(types=["error", "warn"])
|
||||
|
||||
# Include preserved messages
|
||||
all_messages = list_console_messages(includePreservedMessages=True)
|
||||
|
||||
# Get specific message
|
||||
details = get_console_message(msgid=1)
|
||||
```
|
||||
|
||||
## Performance Testing
|
||||
|
||||
```python
|
||||
# Start trace with page reload
|
||||
performance_start_trace(reload=True, autoStop=False)
|
||||
|
||||
# Start trace without reload
|
||||
performance_start_trace(reload=False, autoStop=True, filePath="trace.json.gz")
|
||||
|
||||
# Stop trace
|
||||
results = performance_stop_trace()
|
||||
|
||||
# Stop and save
|
||||
performance_stop_trace(filePath="trace-results.json.gz")
|
||||
|
||||
# Analyze specific insight
|
||||
insight = performance_analyze_insight(
|
||||
insightSetId="results.insightSets[0].id",
|
||||
insightName="LCPBreakdown"
|
||||
)
|
||||
```
|
||||
|
||||
## Page Management
|
||||
|
||||
```python
|
||||
# List open pages
|
||||
pages = list_pages()
|
||||
|
||||
# Select a page
|
||||
select_page(pageId=0, bringToFront=True)
|
||||
|
||||
# Create new page
|
||||
new_page(url="http://127.0.0.1:{PORT}/loras")
|
||||
|
||||
# Close page (keep at least one open!)
|
||||
close_page(pageId=1)
|
||||
|
||||
# Resize page
|
||||
resize_page(width=1920, height=1080)
|
||||
```
|
||||
|
||||
## Screenshots
|
||||
|
||||
```python
|
||||
# Full page screenshot
|
||||
take_screenshot(fullPage=True)
|
||||
|
||||
# Viewport screenshot
|
||||
take_screenshot()
|
||||
|
||||
# Element screenshot
|
||||
take_screenshot(uid="lora-card-1")
|
||||
|
||||
# Save to file
|
||||
take_screenshot(filePath="screenshots/page.png", format="png")
|
||||
|
||||
# JPEG with quality
|
||||
take_screenshot(filePath="screenshots/page.jpg", format="jpeg", quality=90)
|
||||
```
|
||||
|
||||
## Dialog Handling
|
||||
|
||||
```python
|
||||
# Accept dialog
|
||||
handle_dialog(action="accept")
|
||||
|
||||
# Accept with text input
|
||||
handle_dialog(action="accept", promptText="user input")
|
||||
|
||||
# Dismiss dialog
|
||||
handle_dialog(action="dismiss")
|
||||
```
|
||||
|
||||
## Device Emulation
|
||||
|
||||
```python
|
||||
# Mobile viewport
|
||||
emulate(viewport={"width": 375, "height": 667, "isMobile": True, "hasTouch": True})
|
||||
|
||||
# Tablet viewport
|
||||
emulate(viewport={"width": 768, "height": 1024, "isMobile": True, "hasTouch": True})
|
||||
|
||||
# Desktop viewport
|
||||
emulate(viewport={"width": 1920, "height": 1080})
|
||||
|
||||
# Network throttling
|
||||
emulate(networkConditions="Slow 3G")
|
||||
emulate(networkConditions="Fast 4G")
|
||||
|
||||
# CPU throttling
|
||||
emulate(cpuThrottlingRate=4) # 4x slowdown
|
||||
|
||||
# Geolocation
|
||||
emulate(geolocation={"latitude": 37.7749, "longitude": -122.4194})
|
||||
|
||||
# User agent
|
||||
emulate(userAgent="Mozilla/5.0 (Custom)")
|
||||
|
||||
# Reset emulation
|
||||
emulate(viewport=None, networkConditions="No emulation", userAgent=None)
|
||||
```
|
||||
|
||||
## Drag and Drop
|
||||
|
||||
```python
|
||||
# Drag element to another
|
||||
drag(from_uid="draggable-item", to_uid="drop-zone")
|
||||
```
|
||||
|
||||
## Common LoRa Manager Test Patterns
|
||||
|
||||
### Verify LoRA Cards Loaded
|
||||
|
||||
```python
|
||||
navigate_page(type="url", url="http://127.0.0.1:{PORT}/loras")
|
||||
wait_for(text="LoRAs", timeout=10000)
|
||||
|
||||
# Check if cards loaded
|
||||
result = evaluate_script(function="""
|
||||
() => {
|
||||
const cards = document.querySelectorAll('.lora-card');
|
||||
return {
|
||||
count: cards.length,
|
||||
hasData: cards.length > 0
|
||||
};
|
||||
}
|
||||
""")
|
||||
```
|
||||
|
||||
### Search and Verify Results
|
||||
|
||||
```python
|
||||
fill(uid="search-input", value="character")
|
||||
press_key(key="Enter")
|
||||
wait_for(timeout=2000) # Wait for debounce
|
||||
|
||||
# Check results
|
||||
result = evaluate_script(function="""
|
||||
() => {
|
||||
const cards = document.querySelectorAll('.lora-card');
|
||||
const names = Array.from(cards).map(c => c.dataset.name || c.textContent);
|
||||
return { count: cards.length, names };
|
||||
}
|
||||
""")
|
||||
```
|
||||
|
||||
### Check API Response
|
||||
|
||||
```python
|
||||
# Trigger API call
|
||||
evaluate_script(function="""
|
||||
() => window.loraApiCallPromise = fetch('/loras/api/list').then(r => r.json())
|
||||
""")
|
||||
|
||||
# Wait and get result
|
||||
import time
|
||||
time.sleep(1)
|
||||
|
||||
result = evaluate_script(function="""
|
||||
async () => await window.loraApiCallPromise
|
||||
""")
|
||||
```
|
||||
|
||||
### Monitor Console for Errors
|
||||
|
||||
```python
|
||||
# Before test: clear console (navigate reloads)
|
||||
navigate_page(type="reload")
|
||||
|
||||
# ... perform actions ...
|
||||
|
||||
# Check for errors
|
||||
errors = list_console_messages(types=["error"])
|
||||
assert len(errors) == 0, f"Console errors: {errors}"
|
||||
```
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
### Stale profile lock ("browser is already running" / `list_pages` fails)
|
||||
|
||||
A Chrome profile held by a stale Chrome from a prior MCP session makes `list_pages`
|
||||
fail with "browser is already running". Fix:
|
||||
|
||||
1. Find the stale Chrome that owns the profile dir (e.g. `~/.config/chrome-dev-profile`):
|
||||
```bash
|
||||
ps -ef | grep -i '[c]hrome.*user-data-dir'
|
||||
```
|
||||
2. Confirm it is a QA Chrome from a completed task (NOT the live ComfyUI server, NOT
|
||||
your current MCP instance).
|
||||
3. Kill ONLY that stale Chrome (`kill <stale-pid>`), then retry `list_pages`.
|
||||
|
||||
### Screenshot-write restrictions
|
||||
|
||||
The MCP may refuse to write into paths outside its configured workspace roots
|
||||
(e.g. `.omo/evidence/screenshots/` under a worktree that canonicalizes to an unmapped
|
||||
path). Save the screenshot to `/tmp` via the MCP, then copy it into the evidence dir:
|
||||
|
||||
```bash
|
||||
# MCP: take_screenshot(filePath="/tmp/<plan>-e2e/recipe-b-after.png", format="png")
|
||||
# Shell:
|
||||
mkdir -p <repo-root>/.omo/evidence/screenshots
|
||||
cp /tmp/<plan>-e2e/recipe-b-after.png <repo-root>/.omo/evidence/screenshots/
|
||||
```
|
||||
|
||||
### Time budgets & abort rule
|
||||
|
||||
See SKILL.md "Time Budgets & Abort Guidance": if a phase exceeds ~2x its budget or a
|
||||
tool call retries 3+ times in a row, STOP and report BLOCKED with the last observed
|
||||
state (server PID + `ss -tlnp`, page snapshot, last API response). Do not loop.
|
||||
@@ -1,72 +0,0 @@
|
||||
# Recipe Rematch/Repair E2E — Fixtures, Fresh State, Known Gaps
|
||||
|
||||
Specialized guidance for recipe rematch/repair E2E runs, extracted from the SKILL.md
|
||||
main flow. Read the SKILL.md SANDBOX section first — everything here assumes a
|
||||
sandboxed run.
|
||||
|
||||
## Fixture Rules (validated by the task-8 E2E)
|
||||
|
||||
Seed the **sandboxed** `recipes_path` with hand-written fixture recipes:
|
||||
|
||||
1. **Filename constraint**: each file MUST be named `f"{id}.recipe.json"` **and** the
|
||||
in-JSON `id` field MUST equal the filename. Discovery accepts any `*.recipe.json`,
|
||||
but persistence resolves the path via `get_recipe_json_path` and
|
||||
`_save_recipe_persistently` returns `False` on a mismatch → the fixture would be
|
||||
counted as an error.
|
||||
- `recipe-a.recipe.json` → in-JSON `"id": "recipe-a"`
|
||||
2. **File format**: mirror an existing recipe JSON — top-level `id`, `file_path`,
|
||||
`title`, `loras`, `fingerprint`, `gen_params`; lora entries per the persistence
|
||||
conventions (`hash`, `file_name`, `modelVersionId`, `isDeleted`, ...).
|
||||
3. **Companion image**: each recipe needs an image (e.g. a `.webp` generated with PIL)
|
||||
referenced by `file_path`, used for EXIF verification
|
||||
(`ExifUtils.append_recipe_metadata` writes a `"Recipe metadata: ..."` marker; a
|
||||
freshly generated `.webp` with no marker is the clean "untouched" control).
|
||||
4. **autov3 three-state contract**: for L3 (autov3-only, renamed-file) fixtures the
|
||||
local model's `.metadata.json` sidecar MUST have the `autov3` key **ABSENT** (the
|
||||
"unchecked" state), NOT `""` — `""` is the TERMINAL "checked but unavailable" state
|
||||
that L3 deliberately skips. The scanner computes + persists `autov3` from the file
|
||||
header during the normal library scan (`model_scanner.py` `_process_model_file`), so
|
||||
the live L3 match resolves through the local autov3/hash cache; the
|
||||
computed-autov3 branch for unchecked items is covered by the unit suite.
|
||||
5. **Fixture design for a rematch run** (mirrors the task-8 E2E):
|
||||
- `recipe-a`: lora entry `isDeleted=True`, `hash` = 12-char autov3 computed from the
|
||||
local model (`calculate_autov3`, `py/utils/file_utils.py`), whose local model file
|
||||
was RENAMED after the recipe was written so `file_name` differs (proves L3 match
|
||||
without filename).
|
||||
- `recipe-b`: parser-convention checkpoint entry (uses `id`, no `modelVersionId`)
|
||||
matching a local checkpoint via L2 — the local checkpoint's `.metadata.json` MUST
|
||||
carry civitai version data with that `id` so `version_index` contains it (L2
|
||||
cannot match otherwise).
|
||||
- `recipe-c`: healthy recipe (no deleted entries) → must remain untouched.
|
||||
|
||||
The scanner computes and persists model hashes during the library scan, so the sandbox
|
||||
model dirs just need the model files + `.metadata.json` sidecars. With
|
||||
`--settings-path`, all derived data lands under the sandbox settings dir (`cache/`,
|
||||
`backups/`, `logs/`, `stats/`, `wildcards/`), and NO `cache/` appears in the repo root.
|
||||
|
||||
## Fresh State Between Entry-Point Runs
|
||||
|
||||
Each entry point (global / per-recipe / selection-bulk) must start from the same
|
||||
deleted state. Between runs (keep a pristine copy in `<sandbox>/recipes-before/`):
|
||||
|
||||
```bash
|
||||
# 1. Reset fixtures to the before-state snapshot
|
||||
cp <sandbox>/recipes-before/*.recipe.json <sandbox>/recipes/
|
||||
# 2. Clear the recipe/FTS caches (with --settings-path these live under the sandbox
|
||||
# settings dir, NOT <repo-root>/cache)
|
||||
rm -f <sandbox>/settings/cache/recipe/*.sqlite
|
||||
rm -rf <sandbox>/settings/cache/fts/*
|
||||
# 3. Restart the server (fresh process, fresh scan)
|
||||
python .agents/skills/lora-manager-e2e/scripts/start_server.py \
|
||||
--port {PORT} --settings-path <sandbox>/settings --restart --wait --timeout 30 --detach
|
||||
# 4. Re-verify the server is listening + reload the browser page
|
||||
```
|
||||
|
||||
## Cancellation Testing (KNOWN GAP)
|
||||
|
||||
Testing the rematch-cancel path E2E requires a run long enough to cancel mid-flight. A
|
||||
tiny 3-recipe fixture set completes in **seconds** — too fast to reliably cancel. The
|
||||
cancel path is currently **unit-covered only** (`rematch_all_recipes` cancellation
|
||||
tests); do not block an E2E run on cancel-path verification. If you must attempt it,
|
||||
you would need an artificially large/deferred fixture set to create a cancellable
|
||||
window — treat this as a research task, not part of the standard E2E.
|
||||
@@ -1,280 +0,0 @@
|
||||
# LoRa Manager E2E Test Scenarios
|
||||
|
||||
This document provides detailed test scenarios for end-to-end validation of LoRa Manager features.
|
||||
|
||||
> **Run preconditions (from SKILL.md)**: every run uses the **sandboxed** standalone
|
||||
> server on a free port `{PORT}` (default candidate `8188`, only if actually free — pick
|
||||
> e.g. `8199` when `8188` is occupied by a live ComfyUI). Fixtures live in the sandboxed
|
||||
> `recipes_path` as `f"{id}.recipe.json"` files with matching in-JSON `id`; the real user
|
||||
> config and real library are never touched (record protection proof before/after).
|
||||
> Abort if a phase exceeds ~2x its budget or a tool call retries 3+ times (SKILL.md
|
||||
> "Time Budgets & Abort Guidance").
|
||||
|
||||
## Table of Contents
|
||||
|
||||
1. [LoRA List Page](#lora-list-page)
|
||||
2. [Model Details](#model-details)
|
||||
3. [Recipes](#recipes)
|
||||
4. [Settings](#settings)
|
||||
5. [Import/Export](#importexport)
|
||||
|
||||
---
|
||||
|
||||
## LoRA List Page
|
||||
|
||||
### Scenario: Page Load and Display
|
||||
|
||||
**Objective**: Verify the LoRA list page loads correctly and displays models.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to `http://127.0.0.1:{PORT}/loras`
|
||||
2. Wait for page title "LoRAs" to appear
|
||||
3. Take snapshot to verify:
|
||||
- Header with "LoRAs" title is visible
|
||||
- Search/filter controls are present
|
||||
- Grid/list view toggle exists
|
||||
- LoRA cards are displayed (if models exist)
|
||||
- Pagination controls (if applicable)
|
||||
|
||||
**Expected Result**: Page loads without errors, UI elements are present.
|
||||
|
||||
### Scenario: Search Functionality
|
||||
|
||||
**Objective**: Verify search filters LoRA models correctly.
|
||||
|
||||
**Steps**:
|
||||
1. Ensure at least one LoRA exists with known name (e.g., "test-character")
|
||||
2. Navigate to LoRA list page
|
||||
3. Enter search term in search box: "test"
|
||||
4. Press Enter or click search button
|
||||
5. Wait for results to update
|
||||
|
||||
**Expected Result**: Only LoRAs matching search term are displayed.
|
||||
|
||||
**Verification Script**:
|
||||
```python
|
||||
# After search, verify filtered results
|
||||
evaluate_script(function="""
|
||||
() => {
|
||||
const cards = document.querySelectorAll('.lora-card');
|
||||
const names = Array.from(cards).map(c => c.dataset.name);
|
||||
return { count: cards.length, names };
|
||||
}
|
||||
""")
|
||||
```
|
||||
|
||||
### Scenario: Filter by Tags
|
||||
|
||||
**Objective**: Verify tag filtering works correctly.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to LoRA list page
|
||||
2. Click on a tag (e.g., "character", "style")
|
||||
3. Wait for filtered results
|
||||
|
||||
**Expected Result**: Only LoRAs with selected tag are displayed.
|
||||
|
||||
### Scenario: View Mode Toggle
|
||||
|
||||
**Objective**: Verify grid/list view toggle works.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to LoRA list page
|
||||
2. Click list view button
|
||||
3. Verify list layout
|
||||
4. Click grid view button
|
||||
5. Verify grid layout
|
||||
|
||||
**Expected Result**: View mode changes correctly, layout updates.
|
||||
|
||||
---
|
||||
|
||||
## Model Details
|
||||
|
||||
### Scenario: Open Model Details
|
||||
|
||||
**Objective**: Verify clicking a LoRA opens its details.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to LoRA list page
|
||||
2. Click on a LoRA card
|
||||
3. Wait for details panel/modal to open
|
||||
|
||||
**Expected Result**: Details panel shows:
|
||||
- Model name
|
||||
- Preview image
|
||||
- Metadata (trigger words, tags, etc.)
|
||||
- Action buttons (edit, delete, etc.)
|
||||
|
||||
### Scenario: Edit Model Metadata
|
||||
|
||||
**Objective**: Verify metadata editing works end-to-end.
|
||||
|
||||
**Steps**:
|
||||
1. Open a LoRA's details
|
||||
2. Click "Edit" button
|
||||
3. Modify trigger words field
|
||||
4. Add/remove tags
|
||||
5. Save changes
|
||||
6. Refresh page
|
||||
7. Reopen the same LoRA
|
||||
|
||||
**Expected Result**: Changes persist after refresh.
|
||||
|
||||
### Scenario: Delete Model
|
||||
|
||||
**Objective**: Verify model deletion works.
|
||||
|
||||
**Steps**:
|
||||
1. Open a LoRA's details
|
||||
2. Click "Delete" button
|
||||
3. Confirm deletion in dialog
|
||||
4. Wait for removal
|
||||
|
||||
**Expected Result**: Model removed from list, success message shown.
|
||||
|
||||
---
|
||||
|
||||
## Recipes
|
||||
|
||||
### Scenario: Recipe List Display
|
||||
|
||||
**Objective**: Verify recipes page loads and displays recipes.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to `http://127.0.0.1:{PORT}/recipes`
|
||||
2. Wait for "Recipes" title
|
||||
3. Take snapshot
|
||||
|
||||
**Expected Result**: Recipe list displayed with cards/items.
|
||||
|
||||
### Scenario: Create New Recipe
|
||||
|
||||
**Objective**: Verify recipe creation workflow.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to recipes page
|
||||
2. Click "New Recipe" button
|
||||
3. Fill recipe form:
|
||||
- Name: "Test Recipe"
|
||||
- Description: "E2E test recipe"
|
||||
- Add LoRA models
|
||||
4. Save recipe
|
||||
5. Verify recipe appears in list
|
||||
|
||||
**Expected Result**: New recipe created and displayed.
|
||||
|
||||
### Scenario: Apply Recipe
|
||||
|
||||
**Objective**: Verify applying a recipe to ComfyUI.
|
||||
|
||||
**Steps**:
|
||||
1. Open a recipe
|
||||
2. Click "Apply" or "Load in ComfyUI"
|
||||
3. Verify action completes
|
||||
|
||||
**Expected Result**: Recipe applied successfully.
|
||||
|
||||
---
|
||||
|
||||
## Settings
|
||||
|
||||
### Scenario: Settings Page Load
|
||||
|
||||
**Objective**: Verify settings page displays correctly.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to `http://127.0.0.1:{PORT}/settings`
|
||||
2. Wait for "Settings" title
|
||||
3. Take snapshot
|
||||
|
||||
**Expected Result**: Settings form with various options displayed.
|
||||
|
||||
### Scenario: Change Setting and Restart
|
||||
|
||||
**Objective**: Verify settings persist after restart.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to settings page
|
||||
2. Change a setting (e.g., default view mode)
|
||||
3. Save settings
|
||||
4. Restart server: `python scripts/start_server.py --port {PORT} --restart --wait --timeout 30 --detach`
|
||||
5. Refresh browser page
|
||||
6. Navigate to settings
|
||||
|
||||
**Expected Result**: Changed setting value persists.
|
||||
|
||||
---
|
||||
|
||||
## Import/Export
|
||||
|
||||
### Scenario: Export Models List
|
||||
|
||||
**Objective**: Verify export functionality.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to LoRA list
|
||||
2. Click "Export" button
|
||||
3. Select format (JSON/CSV)
|
||||
4. Download file
|
||||
|
||||
**Expected Result**: File downloaded with correct data.
|
||||
|
||||
### Scenario: Import Models
|
||||
|
||||
**Objective**: Verify import functionality.
|
||||
|
||||
**Steps**:
|
||||
1. Prepare import file
|
||||
2. Navigate to import page
|
||||
3. Upload file
|
||||
4. Verify import results
|
||||
|
||||
**Expected Result**: Models imported successfully, confirmation shown.
|
||||
|
||||
---
|
||||
|
||||
## API Integration Tests
|
||||
|
||||
### Scenario: Verify API Endpoints
|
||||
|
||||
**Objective**: Verify backend API responds correctly.
|
||||
|
||||
**Test via browser console**:
|
||||
```javascript
|
||||
// List LoRAs
|
||||
fetch('/loras/api/list').then(r => r.json()).then(console.log)
|
||||
|
||||
// Get LoRA details
|
||||
fetch('/loras/api/detail/<id>').then(r => r.json()).then(console.log)
|
||||
|
||||
// Search LoRAs
|
||||
fetch('/loras/api/search?q=test').then(r => r.json()).then(console.log)
|
||||
```
|
||||
|
||||
**Expected Result**: APIs return valid JSON with expected structure.
|
||||
|
||||
---
|
||||
|
||||
## Console Error Monitoring
|
||||
|
||||
During all tests, monitor browser console for errors:
|
||||
|
||||
```python
|
||||
# Check for JavaScript errors
|
||||
messages = list_console_messages(types=["error"])
|
||||
assert len(messages) == 0, f"Console errors found: {messages}"
|
||||
```
|
||||
|
||||
## Network Request Verification
|
||||
|
||||
Verify key API calls are made:
|
||||
|
||||
```python
|
||||
# List XHR requests
|
||||
requests = list_network_requests(resourceTypes=["xhr", "fetch"])
|
||||
|
||||
# Look for specific endpoints
|
||||
lora_list_requests = [r for r in requests if "/api/list" in r.get("url", "")]
|
||||
assert len(lora_list_requests) > 0, "LoRA list API not called"
|
||||
```
|
||||
@@ -1,215 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Example E2E test demonstrating LoRa Manager testing workflow.
|
||||
|
||||
This script shows how to:
|
||||
1. Start the standalone server
|
||||
2. Use Chrome DevTools MCP to interact with the UI
|
||||
3. Verify functionality end-to-end
|
||||
|
||||
Note: This is a template. Actual execution requires Chrome DevTools MCP.
|
||||
|
||||
Port: pick a FREE port for the run — 8188 is commonly occupied by a live
|
||||
ComfyUI (see the skill's Port Selection section). Set PORT below to e.g. 8199
|
||||
when 8188 is taken. Always run against a SANDBOXED standalone server.
|
||||
"""
|
||||
|
||||
import subprocess
|
||||
import sys
|
||||
|
||||
# Choose the E2E port. 8188 is only the default candidate; use 8199 (or any
|
||||
# free port checked with `ss -tlnp`) when 8188 is occupied by a live ComfyUI.
|
||||
PORT = "8188"
|
||||
|
||||
|
||||
def run_test():
|
||||
"""Run example E2E test flow."""
|
||||
|
||||
print("=" * 60)
|
||||
print("LoRa Manager E2E Test Example")
|
||||
print("=" * 60)
|
||||
|
||||
# Step 1: Start server (detached so it survives the shell)
|
||||
print("\n[1/5] Starting LoRa Manager standalone server...")
|
||||
result = subprocess.run(
|
||||
[sys.executable, "start_server.py", "--port", PORT, "--wait", "--timeout", "30", "--detach"],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
)
|
||||
if result.returncode != 0:
|
||||
print(f"Failed to start server: {result.stderr}")
|
||||
return 1
|
||||
print("Server ready!")
|
||||
|
||||
# Step 2: Open Chrome (manual step - show command)
|
||||
print("\n[2/5] Open Chrome with debug mode:")
|
||||
print(
|
||||
f"google-chrome --remote-debugging-port=9222 "
|
||||
f"--user-data-dir=/tmp/chrome-lora-manager http://127.0.0.1:{PORT}/loras"
|
||||
)
|
||||
print("(In actual test, this would be automated via MCP)")
|
||||
|
||||
# Step 3: Navigate and verify page load
|
||||
print("\n[3/5] Page Load Verification:")
|
||||
print(
|
||||
f"""
|
||||
MCP Commands to execute:
|
||||
1. navigate_page(type="url", url="http://127.0.0.1:{PORT}/loras")
|
||||
2. wait_for(text="LoRAs", timeout=10000)
|
||||
3. snapshot = take_snapshot()
|
||||
"""
|
||||
)
|
||||
|
||||
# Step 4: Test search functionality
|
||||
print("\n[4/5] Search Functionality Test:")
|
||||
print(
|
||||
"""
|
||||
MCP Commands to execute:
|
||||
1. fill(uid="search-input", value="test")
|
||||
2. press_key(key="Enter")
|
||||
3. wait_for(text="Results", timeout=5000)
|
||||
4. result = evaluate_script(function=`
|
||||
() => {
|
||||
const cards = document.querySelectorAll('.lora-card');
|
||||
return { count: cards.length };
|
||||
}
|
||||
`)
|
||||
"""
|
||||
)
|
||||
|
||||
# Step 5: Verify API
|
||||
print("\n[5/5] API Verification:")
|
||||
print(
|
||||
"""
|
||||
MCP Commands to execute:
|
||||
1. api_result = evaluate_script(function=`
|
||||
async () => {
|
||||
const response = await fetch('/loras/api/list');
|
||||
const data = await response.json();
|
||||
return { count: data.length, status: response.status };
|
||||
}
|
||||
`)
|
||||
2. Verify api_result['status'] == 200
|
||||
"""
|
||||
)
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("Test flow completed!")
|
||||
print("=" * 60)
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
def example_restart_flow():
|
||||
"""Example: Testing configuration change that requires restart."""
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("Example: Server Restart Flow")
|
||||
print("=" * 60)
|
||||
|
||||
print(
|
||||
f"""
|
||||
Scenario: Change setting and verify after restart
|
||||
|
||||
Steps:
|
||||
1. Navigate to settings page
|
||||
- navigate_page(type="url", url="http://127.0.0.1:{PORT}/settings")
|
||||
|
||||
2. Change a setting (e.g., theme)
|
||||
- fill(uid="theme-select", value="dark")
|
||||
- click(uid="save-settings-button")
|
||||
|
||||
3. Restart server
|
||||
- subprocess.run([python, "start_server.py", "--port", "{PORT}", "--restart", "--wait", "--detach"])
|
||||
|
||||
4. Refresh browser
|
||||
- navigate_page(type="reload", ignoreCache=True)
|
||||
- wait_for(text="LoRAs", timeout=15000)
|
||||
|
||||
5. Verify setting persisted
|
||||
- navigate_page(type="url", url="http://127.0.0.1:{PORT}/settings")
|
||||
- theme = evaluate_script(function="() => document.querySelector('#theme-select').value")
|
||||
- assert theme == "dark"
|
||||
"""
|
||||
)
|
||||
|
||||
|
||||
def example_modal_interaction():
|
||||
"""Example: Testing modal dialog interaction."""
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("Example: Modal Dialog Interaction")
|
||||
print("=" * 60)
|
||||
|
||||
print(
|
||||
"""
|
||||
Scenario: Add new LoRA via modal
|
||||
|
||||
Steps:
|
||||
1. Open modal
|
||||
- click(uid="add-lora-button")
|
||||
- wait_for(text="Add LoRA", timeout=3000)
|
||||
|
||||
2. Fill form
|
||||
- fill_form(elements=[
|
||||
{"uid": "lora-name", "value": "Test Character"},
|
||||
{"uid": "lora-path", "value": "/models/test.safetensors"},
|
||||
])
|
||||
|
||||
3. Submit
|
||||
- click(uid="modal-submit-button")
|
||||
|
||||
4. Verify success
|
||||
- wait_for(text="Successfully added", timeout=5000)
|
||||
- snapshot = take_snapshot()
|
||||
"""
|
||||
)
|
||||
|
||||
|
||||
def example_network_monitoring():
|
||||
"""Example: Network request monitoring."""
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("Example: Network Request Monitoring")
|
||||
print("=" * 60)
|
||||
|
||||
print(
|
||||
f"""
|
||||
Scenario: Verify API calls during user interaction
|
||||
|
||||
Steps:
|
||||
1. Clear network log (implicit on navigation)
|
||||
- navigate_page(type="url", url="http://127.0.0.1:{PORT}/loras")
|
||||
|
||||
2. Perform action that triggers API call
|
||||
- fill(uid="search-input", value="character")
|
||||
- press_key(key="Enter")
|
||||
|
||||
3. List network requests
|
||||
- requests = list_network_requests(resourceTypes=["xhr", "fetch"])
|
||||
|
||||
4. Find search API call
|
||||
- search_requests = [r for r in requests if "/api/search" in r.get("url", "")]
|
||||
- assert len(search_requests) > 0, "Search API was not called"
|
||||
|
||||
5. Get request details
|
||||
- if search_requests:
|
||||
details = get_network_request(reqid=search_requests[0]["reqid"])
|
||||
- Verify request method, response status, etc.
|
||||
"""
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("LoRa Manager E2E Test Examples\n")
|
||||
print("This script demonstrates E2E testing patterns.\n")
|
||||
print("Note: Actual execution requires Chrome DevTools MCP connection.\n")
|
||||
|
||||
run_test()
|
||||
example_restart_flow()
|
||||
example_modal_interaction()
|
||||
example_network_monitoring()
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("All examples shown!")
|
||||
print("=" * 60)
|
||||
@@ -170,6 +170,10 @@ The system runs in two modes:
|
||||
- Route registrars organize endpoints by domain: `ModelRouteRegistrar`, `RecipeRouteRegistrar`, etc.
|
||||
- Request handlers in `py/routes/handlers/` implement route logic
|
||||
- All routes use aiohttp, return `web.json_response` or `web.Response`
|
||||
- Endpoints consumed by the companion browser extension (lm-civitai-extension)
|
||||
MUST also accept `GET` with query-string params: the extension is GET-only by
|
||||
convention (see its AGENTS.md), even for state-changing operations such as
|
||||
`GET /api/lm/recipe/{recipe_id}/reimport`
|
||||
|
||||
### Recipe System
|
||||
|
||||
@@ -215,6 +219,26 @@ The system runs in two modes:
|
||||
- Vanilla JS tests: `tests/frontend/**/*.test.js` with jsdom; setup in `tests/frontend/setup.js`
|
||||
- Vue widget tests: `vue-widgets/tests/**/*.test.ts` with jsdom + `@vue/test-utils`
|
||||
|
||||
### UI Verification (manual default)
|
||||
|
||||
UI/layout changes are verified by the user by eye — do NOT spin up a sandbox,
|
||||
standalone server, or browser automation to "prove" a visual fix. Ask the user to
|
||||
look instead. The full browser E2E ceremony (server + Chrome DevTools MCP +
|
||||
screenshots) is slow, token-heavy, and fragile; reserve it for genuine
|
||||
server+browser integration bugs, and only when the user explicitly agrees.
|
||||
|
||||
If a cross-layer issue ever needs a live server, the sandboxed helpers live in
|
||||
`scripts/e2e/` (`start_server.py`, `wait_for_server.py`). Non-negotiable rules:
|
||||
|
||||
- Always launch with `--settings-path <sandbox>/settings` and sandboxed
|
||||
`folder_paths` under `/tmp` — the repo folder is the real plugin folder and a
|
||||
`settings.json` there is read by the live instance. Never touch real config or
|
||||
real model libraries.
|
||||
- Never kill a process you did not start; `start_server.py` tracks its own PIDs
|
||||
via pidfile and refuses to touch unrelated processes on the port.
|
||||
- Abort after ~30 minutes or 3 consecutive tool failures; report `BLOCKED` with
|
||||
observed state instead of retrying blindly. Clean up sandbox and server after.
|
||||
|
||||
## Key Integration Points
|
||||
|
||||
- **Settings:** Stored in the user config directory (via `platformdirs`) or portable mode (`"use_portable_settings": true`)
|
||||
|
||||
+427
-395
File diff suppressed because it is too large
Load Diff
@@ -137,7 +137,7 @@ and must be normalized. `en` = keep the English word as-is.
|
||||
|
||||
| Term | Use | Fix |
|
||||
|---|---|---|
|
||||
| recipe | Rezept/Rezepte | 5 leftover English "Recipe" keys → Rezept (e.g. `globalContextMenu.repairRecipes.label`, `toast.recipes.recipeSaved`) |
|
||||
| recipe | Rezept/Rezepte | leftover English "Recipe" keys → Rezept (e.g. `toast.recipes.recipeSaved`) |
|
||||
| base model | pick Basis-Modell or Basismodell | currently 27× hyphenated vs 15× closed |
|
||||
| metadata | Metadaten | 4 keys use "Modelldaten" (`onboarding.steps.fetch.title/content`) → Metadaten |
|
||||
| bulk | pick Massen- or Sammelmodus | `loras.controls.bulk.action` = "Massen" reads as "crowds" — use "Massenbearbeitung"/"Mehrfachauswahl" |
|
||||
@@ -193,7 +193,7 @@ and must be normalized. `en` = keep the English word as-is.
|
||||
| Checkpoint | Checkpoint or チェックポイント (pick one) | 3 variants: Checkpoint (~14), checkpoint lowercase (4), チェックポイント (4, e.g. `settings.priorityTags.modelTypes.checkpoint`) |
|
||||
| Embedding | Embedding | 4 keys lowercase "embedding" mid-sentence |
|
||||
| bulk | 一括 | `modals.checkUpdates.tip` "バルクモード" → 一括モード |
|
||||
| recipe counter | 件 or 個 | `repairRecipes.success` uses 件, `.cancelled` uses 個 — unify |
|
||||
| recipe counter | 件 or 個 | `globalContextMenu.rematchRecipes.success` uses 件, `.cancelled` uses 個 — unify |
|
||||
|
||||
### ko
|
||||
|
||||
|
||||
@@ -0,0 +1,58 @@
|
||||
# CivitAI image imports can end up with 0 LoRAs
|
||||
|
||||
## Symptom
|
||||
|
||||
Importing a CivitAI image URL can produce a recipe with **zero LoRA
|
||||
entries**, even though the image page lists LoRAs in its resource panel.
|
||||
|
||||
Reported example: `https://civitai.red/images/140818889` was imported as a
|
||||
local recipe with 0 LoRAs, while the page shows 3 LoRAs. Some images (e.g.
|
||||
NSFW / higher browsing level) additionally require a login to view, so their
|
||||
data is not publicly reachable at all.
|
||||
|
||||
## Root cause
|
||||
|
||||
URL imports use only two data sources:
|
||||
|
||||
1. **CivitAI REST image API** — `GET /api/v1/images?imageId=<id>&nsfw=X&withMeta=true` → `meta`
|
||||
2. **Embedded image metadata** — EXIF/XMP read from the downloaded bytes
|
||||
|
||||
For the same image both sources can be empty, and the one source that does
|
||||
contain the data is never queried. Verified for image 140818889:
|
||||
|
||||
| Source | What it returned |
|
||||
|---|---|
|
||||
| REST image API | `meta` holds only a prompt; `modelVersionIds: []`; no `resources`/`hashes`; `baseModel: null` |
|
||||
| Downloaded image | PNG with **no EXIF/XMP** (the CDN URL ends in `.jpeg`, the body is PNG) |
|
||||
| Image page HTML | `__NEXT_DATA__` embeds the trpc `image.getGenerationData` result → full `resources` list: 3 LoRAs, each with `modelId`, `modelVersionId`, `modelName`, `modelType`, `versionName`, `baseModel` |
|
||||
|
||||
Key points:
|
||||
|
||||
- The page's resource panel is fed by an **internal, non-public trpc
|
||||
endpoint**, not by the public REST image API.
|
||||
- That internal endpoint is **login-gated** for some content — the
|
||||
"requires login" symptom.
|
||||
- Even with the version IDs in hand, `/model-versions/{id}` for these
|
||||
(Krea) versions returns **no `sha256`**, so an exact local-file hash match
|
||||
is impossible; only model/version identity is recoverable.
|
||||
|
||||
## Conclusion / status
|
||||
|
||||
0-LoRA imports are a data-source gap: public REST meta and image EXIF are
|
||||
both empty, while the only complete source (page generation data) is
|
||||
internal, sometimes login-gated, and not used by the importer.
|
||||
|
||||
Such imports **cannot be reliably auto-repaired/completed** by the backend
|
||||
alone. The old "Repair Metadata" feature only re-fetched the same incomplete
|
||||
REST meta and could not fix them; it was deprecated and has been removed.
|
||||
|
||||
**Fixed via the companion browser extension.** When the extension is
|
||||
installed with a valid license, it scrapes the image page's internal trpc
|
||||
generation data with the user's session and calls the payload-capable
|
||||
re-import endpoint (`POST /api/lm/recipe/{recipe_id}/reimport` with
|
||||
`image_url`/`name`/`resources`/`gen_params`/`base_model`/`tags` query
|
||||
params), which rebuilds the recipe from the caller-supplied metadata. The
|
||||
web UI delegates re-import of CivitAI-image-sourced recipes to the extension
|
||||
automatically (probe + `lm:reimport*` DOM events); without the extension,
|
||||
re-import silently falls back to the native path, which remains limited by
|
||||
the data-source gap documented above.
|
||||
+1
-19
@@ -212,13 +212,6 @@
|
||||
"none": "Alle {typePlural} verfügen bereits über Lizenzmetadaten",
|
||||
"error": "Lizenzmetadaten für {typePlural} konnten nicht aktualisiert werden: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "Rezept-Daten reparieren",
|
||||
"loading": "Rezept-Daten werden repariert...",
|
||||
"success": "{count} Rezepte erfolgreich repariert.",
|
||||
"cancelled": "Reparatur abgebrochen. {count} Rezepte wurden repariert.",
|
||||
"error": "Rezept-Reparatur fehlgeschlagen: {message}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "Rezepte lokalen Modellen neu zuordnen",
|
||||
"loading": "Rezepte werden lokalen Modellen neu zugeordnet...",
|
||||
@@ -821,7 +814,6 @@
|
||||
"setContentRating": "Inhaltsbewertung für alle festlegen",
|
||||
"copyAll": "Alle Syntax kopieren",
|
||||
"refreshAll": "Alle Metadaten aktualisieren",
|
||||
"repairMetadata": "Metadaten der Auswahl reparieren",
|
||||
"rematchMetadata": "Ausgewählte mit lokalen Modellen abgleichen",
|
||||
"reimportMetadata": "Aus Quelle neu importieren",
|
||||
"checkUpdates": "Auswahl auf Updates prüfen",
|
||||
@@ -877,7 +869,6 @@
|
||||
"replacePreview": "Vorschau ersetzen",
|
||||
"setContentRating": "Inhaltsbewertung festlegen",
|
||||
"moveToFolder": "In Ordner verschieben",
|
||||
"repairMetadata": "Metadaten reparieren",
|
||||
"rematchMetadata": "Mit lokalen Modellen abgleichen",
|
||||
"reimportMetadata": "Aus Quelle neu importieren",
|
||||
"excludeModel": "Modell ausschließen",
|
||||
@@ -1130,13 +1121,6 @@
|
||||
"getInfoFailed": "Fehler beim Abrufen der Informationen für fehlende LoRAs",
|
||||
"prepareError": "Fehler beim Vorbereiten der LoRAs für den Download: {message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "Rezept-Metadaten werden repariert...",
|
||||
"success": "Rezept-Metadaten erfolgreich repariert",
|
||||
"skipped": "Rezept bereits in der neuesten Version, keine Reparatur erforderlich",
|
||||
"failed": "Rezept-Reparatur fehlgeschlagen: {message}",
|
||||
"missingId": "Rezept kann nicht repariert werden: Fehlende Rezept-ID"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "Rezept wird aus Quelle neu importiert...",
|
||||
"success": "Rezept erfolgreich neu importiert",
|
||||
@@ -2238,9 +2222,6 @@
|
||||
"batchImportBrowseFailed": "Ordner konnte nicht durchsucht werden: {message}",
|
||||
"batchImportDirectorySelected": "Verzeichnis ausgewählt: {path}",
|
||||
"noRecipesSelected": "Keine Rezepte ausgewählt",
|
||||
"repairBulkComplete": "Reparatur abgeschlossen: {repaired} repariert, {skipped} übersprungen (von {total})",
|
||||
"repairBulkSkipped": "Keine Reparatur für die {total} ausgewählten Rezepte erforderlich",
|
||||
"repairBulkFailed": "Reparatur der ausgewählten Rezepte fehlgeschlagen: {message}",
|
||||
"rematchComplete": "{entries} Einträge in {recipes} Rezepten zugeordnet",
|
||||
"rematchCompleteErrors": "{entries} Einträge in {recipes} Rezepten zugeordnet, {failures} fehlgeschlagen",
|
||||
"rematchAllFailed": "Zuordnung fehlgeschlagen für {failures} von {total} ausgewählten Rezepten",
|
||||
@@ -2248,6 +2229,7 @@
|
||||
"rematchSkipped": "Keine Zuordnung für die {total} ausgewählten Rezepte erforderlich",
|
||||
"rematchFailed": "Zuordnung der ausgewählten Rezepte fehlgeschlagen: {message}",
|
||||
"reimporting": "Rezept wird aus Quelle neu importiert...",
|
||||
"reimportingViaExtension": "Rezept {current}/{total} wird über die Browser-Erweiterung neu importiert...",
|
||||
"reimportSuccess": "Rezept erfolgreich neu importiert",
|
||||
"reimportBulkComplete": "Neuimport abgeschlossen: {completed} importiert, {failed} fehlgeschlagen (von {total})",
|
||||
"reimportBulkFailed": "Neuimport einiger Rezepte fehlgeschlagen",
|
||||
|
||||
+1
-19
@@ -212,13 +212,6 @@
|
||||
"none": "All {typePlural} already have license metadata",
|
||||
"error": "Failed to refresh license metadata for {typePlural}: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "Repair recipes data",
|
||||
"loading": "Repairing recipe data...",
|
||||
"success": "Successfully repaired {count} recipes.",
|
||||
"cancelled": "Repair cancelled. {count} recipes were repaired.",
|
||||
"error": "Recipe repair failed: {message}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "Rematch recipes to local models",
|
||||
"loading": "Rematching recipes to local models...",
|
||||
@@ -821,7 +814,6 @@
|
||||
"setContentRating": "Set Content Rating for Selected",
|
||||
"copyAll": "Copy Selected Syntax",
|
||||
"refreshAll": "Refresh Selected Metadata",
|
||||
"repairMetadata": "Repair Metadata for Selected",
|
||||
"rematchMetadata": "Rematch Selected to Local Models",
|
||||
"reimportMetadata": "Re-import from Source",
|
||||
"checkUpdates": "Check Updates for Selected",
|
||||
@@ -877,7 +869,6 @@
|
||||
"replacePreview": "Replace Preview",
|
||||
"setContentRating": "Set Content Rating",
|
||||
"moveToFolder": "Move to Folder",
|
||||
"repairMetadata": "Repair metadata",
|
||||
"rematchMetadata": "Rematch to local models",
|
||||
"reimportMetadata": "Re-import from Source",
|
||||
"excludeModel": "Exclude Model",
|
||||
@@ -1130,13 +1121,6 @@
|
||||
"getInfoFailed": "Failed to get information for missing LoRAs",
|
||||
"prepareError": "Error preparing LoRAs for download: {message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "Repairing recipe metadata...",
|
||||
"success": "Recipe metadata repaired successfully",
|
||||
"skipped": "Recipe already at latest version, no repair needed",
|
||||
"failed": "Failed to repair recipe: {message}",
|
||||
"missingId": "Cannot repair recipe: Missing recipe ID"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "Re-importing recipe from source...",
|
||||
"success": "Recipe re-imported successfully",
|
||||
@@ -2238,9 +2222,6 @@
|
||||
"batchImportBrowseFailed": "Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"noRecipesSelected": "No recipes selected",
|
||||
"repairBulkComplete": "Repair complete: {repaired} repaired, {skipped} skipped (of {total})",
|
||||
"repairBulkSkipped": "No repair needed for any of the {total} selected recipes",
|
||||
"repairBulkFailed": "Failed to repair selected recipes: {message}",
|
||||
"rematchComplete": "Matched {entries} entries across {recipes} recipes",
|
||||
"rematchCompleteErrors": "Matched {entries} entries across {recipes} recipes, {failures} failed",
|
||||
"rematchAllFailed": "Rematch failed for {failures} of {total} selected recipes",
|
||||
@@ -2248,6 +2229,7 @@
|
||||
"rematchSkipped": "No rematch needed for any of the {total} selected recipes",
|
||||
"rematchFailed": "Failed to rematch selected recipes: {message}",
|
||||
"reimporting": "Re-importing recipe from source...",
|
||||
"reimportingViaExtension": "Re-importing recipe {current}/{total} via browser extension...",
|
||||
"reimportSuccess": "Recipe re-imported successfully",
|
||||
"reimportBulkComplete": "Re-import complete: {completed} re-imported, {failed} failed (of {total})",
|
||||
"reimportBulkFailed": "Failed to re-import some recipes",
|
||||
|
||||
+1
-19
@@ -212,13 +212,6 @@
|
||||
"none": "Todos los {typePlural} ya tienen metadatos de licencia",
|
||||
"error": "No se pudieron actualizar los metadatos de licencia de los {typePlural}: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "Reparar datos de recetas",
|
||||
"loading": "Reparando datos de recetas...",
|
||||
"success": "Se repararon con éxito {count} recetas.",
|
||||
"cancelled": "Reparación cancelada. {count} recetas fueron reparadas.",
|
||||
"error": "Error al reparar recetas: {message}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "Reasociar recetas con modelos locales",
|
||||
"loading": "Reasociando recetas con modelos locales...",
|
||||
@@ -821,7 +814,6 @@
|
||||
"setContentRating": "Establecer clasificación de contenido para todos",
|
||||
"copyAll": "Copiar toda la sintaxis",
|
||||
"refreshAll": "Actualizar todos los metadatos",
|
||||
"repairMetadata": "Reparar metadatos de la selección",
|
||||
"rematchMetadata": "Reasociar los seleccionados con modelos locales",
|
||||
"reimportMetadata": "Reimportar desde origen",
|
||||
"checkUpdates": "Comprobar actualizaciones para la selección",
|
||||
@@ -877,7 +869,6 @@
|
||||
"replacePreview": "Reemplazar vista previa",
|
||||
"setContentRating": "Establecer clasificación de contenido",
|
||||
"moveToFolder": "Mover a carpeta",
|
||||
"repairMetadata": "Reparar metadatos",
|
||||
"rematchMetadata": "Reasociar con modelos locales",
|
||||
"reimportMetadata": "Reimportar desde origen",
|
||||
"excludeModel": "Excluir modelo",
|
||||
@@ -1130,13 +1121,6 @@
|
||||
"getInfoFailed": "Error al obtener información de LoRAs faltantes",
|
||||
"prepareError": "Error preparando LoRAs para descarga: {message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "Reparando metadatos de la receta...",
|
||||
"success": "Metadatos de la receta reparados con éxito",
|
||||
"skipped": "La receta ya está en la última versión, no se necesita reparación",
|
||||
"failed": "Error al reparar la receta: {message}",
|
||||
"missingId": "No se puede reparar la receta: falta el ID de la receta"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "Reimportando receta desde origen...",
|
||||
"success": "Receta reimportada exitosamente",
|
||||
@@ -2238,9 +2222,6 @@
|
||||
"batchImportBrowseFailed": "No se pudo examinar el directorio: {message}",
|
||||
"batchImportDirectorySelected": "Directorio seleccionado: {path}",
|
||||
"noRecipesSelected": "No se han seleccionado recetas",
|
||||
"repairBulkComplete": "Reparación completa: {repaired} reparadas, {skipped} omitidas (de {total})",
|
||||
"repairBulkSkipped": "No se necesita reparación para ninguna de las {total} recetas seleccionadas",
|
||||
"repairBulkFailed": "Error al reparar las recetas seleccionadas: {message}",
|
||||
"rematchComplete": "{entries} entradas asociadas en {recipes} recetas",
|
||||
"rematchCompleteErrors": "{entries} entradas asociadas en {recipes} recetas, {failures} fallidas",
|
||||
"rematchAllFailed": "Falló la reasociación de {failures} de {total} recetas seleccionadas",
|
||||
@@ -2248,6 +2229,7 @@
|
||||
"rematchSkipped": "Ninguna de las {total} recetas seleccionadas necesita reasociación",
|
||||
"rematchFailed": "Falló la reasociación de las recetas seleccionadas: {message}",
|
||||
"reimporting": "Reimportando receta desde origen...",
|
||||
"reimportingViaExtension": "Reimportando receta {current}/{total} mediante la extensión del navegador...",
|
||||
"reimportSuccess": "Receta reimportada exitosamente",
|
||||
"reimportBulkComplete": "Reimportación completa: {completed} reimportadas, {failed} fallidas (de {total})",
|
||||
"reimportBulkFailed": "Error al reimportar algunas recetas",
|
||||
|
||||
+1
-19
@@ -212,13 +212,6 @@
|
||||
"none": "Tous les {typePlural} possèdent déjà des métadonnées de licence",
|
||||
"error": "Échec de l'actualisation des métadonnées de licence pour les {typePlural} : {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "Réparer les données de Recipes",
|
||||
"loading": "Réparation des données de Recipes...",
|
||||
"success": "{count} Recipes réparées avec succès.",
|
||||
"cancelled": "Réparation annulée. {count} Recipes ont été réparées.",
|
||||
"error": "Échec de la réparation des Recipes : {message}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "Réassocier les Recipes aux modèles locaux",
|
||||
"loading": "Réassociation des Recipes aux modèles locaux...",
|
||||
@@ -821,7 +814,6 @@
|
||||
"setContentRating": "Définir la classification du contenu pour tous",
|
||||
"copyAll": "Copier toute la syntaxe",
|
||||
"refreshAll": "Actualiser toutes les métadonnées",
|
||||
"repairMetadata": "Réparer les métadonnées de la sélection",
|
||||
"rematchMetadata": "Réassocier la sélection aux modèles locaux",
|
||||
"reimportMetadata": "Ré-importer depuis la source",
|
||||
"checkUpdates": "Vérifier les mises à jour pour la sélection",
|
||||
@@ -877,7 +869,6 @@
|
||||
"replacePreview": "Remplacer l'aperçu",
|
||||
"setContentRating": "Définir la classification du contenu",
|
||||
"moveToFolder": "Déplacer vers un dossier",
|
||||
"repairMetadata": "Réparer les métadonnées",
|
||||
"rematchMetadata": "Réassocier aux modèles locaux",
|
||||
"reimportMetadata": "Ré-importer depuis la source",
|
||||
"excludeModel": "Exclure le modèle",
|
||||
@@ -1130,13 +1121,6 @@
|
||||
"getInfoFailed": "Échec de l'obtention des informations pour les LoRAs manquants",
|
||||
"prepareError": "Erreur lors de la préparation des LoRAs pour le téléchargement : {message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "Réparation des métadonnées de la Recipe...",
|
||||
"success": "Métadonnées de la Recipe réparées avec succès",
|
||||
"skipped": "Recette déjà à la version la plus récente, aucune réparation nécessaire",
|
||||
"failed": "Échec de la réparation de la Recipe : {message}",
|
||||
"missingId": "Impossible de réparer la Recipe : ID de Recipe manquant"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "Ré-import de la Recipe depuis la source...",
|
||||
"success": "Recette ré-importée avec succès",
|
||||
@@ -2238,9 +2222,6 @@
|
||||
"batchImportBrowseFailed": "Échec de la navigation dans le dossier : {message}",
|
||||
"batchImportDirectorySelected": "Dossier sélectionné : {path}",
|
||||
"noRecipesSelected": "Aucune Recipe sélectionnée",
|
||||
"repairBulkComplete": "Réparation terminée : {repaired} réparée(s), {skipped} ignorée(s) (sur {total})",
|
||||
"repairBulkSkipped": "Aucune réparation nécessaire parmi les {total} Recipes sélectionnées",
|
||||
"repairBulkFailed": "Échec de la réparation des Recipes sélectionnées : {message}",
|
||||
"rematchComplete": "{entries} entrées associées dans {recipes} Recipes",
|
||||
"rematchCompleteErrors": "{entries} entrées associées dans {recipes} Recipes, {failures} échecs",
|
||||
"rematchAllFailed": "Échec de la réassociation de {failures} Recipes sélectionnées sur {total}",
|
||||
@@ -2248,6 +2229,7 @@
|
||||
"rematchSkipped": "Aucune des {total} Recipes sélectionnées ne nécessite de réassociation",
|
||||
"rematchFailed": "Échec de la réassociation des Recipes sélectionnées : {message}",
|
||||
"reimporting": "Ré-import de la Recipe depuis la source...",
|
||||
"reimportingViaExtension": "Ré-import de la Recipe {current}/{total} via l’extension du navigateur...",
|
||||
"reimportSuccess": "Recette ré-importée avec succès",
|
||||
"reimportBulkComplete": "Ré-import terminé : {completed} ré-importé(s), {failed} échec(s) (sur {total})",
|
||||
"reimportBulkFailed": "Échec du ré-import de certaines Recipes",
|
||||
|
||||
+1
-19
@@ -212,13 +212,6 @@
|
||||
"none": "לכל ה-{typePlural} כבר יש מטא-נתוני רישיון",
|
||||
"error": "לא ניתן היה לרענן את מטא-נתוני הרישיון עבור {typePlural}: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "תיקון נתוני מתכונים",
|
||||
"loading": "מתקן נתוני מתכונים...",
|
||||
"success": "תוקנו בהצלחה {count} מתכונים.",
|
||||
"cancelled": "תיקון בוטל. {count} מתכונים תוקנו.",
|
||||
"error": "תיקון המתכונים נכשל: {message}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "התאמה מחדש של מתכונים למודלים מקומיים",
|
||||
"loading": "מתבצעת התאמה מחדש של מתכונים למודלים מקומיים...",
|
||||
@@ -821,7 +814,6 @@
|
||||
"setContentRating": "הגדר דירוג תוכן לכל המודלים",
|
||||
"copyAll": "העתק את כל התחבירים",
|
||||
"refreshAll": "רענן את כל המטא-נתונים",
|
||||
"repairMetadata": "תקן מטא-נתונים עבור הנבחרים",
|
||||
"rematchMetadata": "התאמה מחדש של הנבחרים למודלים מקומיים",
|
||||
"reimportMetadata": "ייבא מחדש ממקור",
|
||||
"checkUpdates": "בדוק עדכונים לבחירה",
|
||||
@@ -877,7 +869,6 @@
|
||||
"replacePreview": "החלף תצוגה מקדימה",
|
||||
"setContentRating": "הגדר דירוג תוכן",
|
||||
"moveToFolder": "העבר לתיקייה",
|
||||
"repairMetadata": "תיקון מטא-נתונים",
|
||||
"rematchMetadata": "התאמה מחדש למודלים מקומיים",
|
||||
"reimportMetadata": "ייבא מחדש ממקור",
|
||||
"excludeModel": "החרג מודל",
|
||||
@@ -1130,13 +1121,6 @@
|
||||
"getInfoFailed": "קבלת מידע עבור LoRAs חסרים נכשלה",
|
||||
"prepareError": "שגיאה בהכנת LoRAs להורדה: {message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "מתקן מטא-נתונים של מתכון...",
|
||||
"success": "מטא-נתונים של מתכון תוקן בהצלחה",
|
||||
"skipped": "המתכון כבר בגרסה העדכנית ביותר, אין צורך בתיקון",
|
||||
"failed": "תיקון המתכון נכשל: {message}",
|
||||
"missingId": "לא ניתן לתקן את המתכון: חסר מזהה מתכון"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "מייבא מתכון מחדש מהמקור...",
|
||||
"success": "המתכון יובא מחדש בהצלחה",
|
||||
@@ -2238,9 +2222,6 @@
|
||||
"batchImportBrowseFailed": "לא ניתן היה לעיין בתיקייה: {message}",
|
||||
"batchImportDirectorySelected": "נבחרה תיקייה: {path}",
|
||||
"noRecipesSelected": "לא נבחרו מתכונים",
|
||||
"repairBulkComplete": "התיקון הושלם: {repaired} תוקנו, {skipped} דולגו (מתוך {total})",
|
||||
"repairBulkSkipped": "אין צורך בתיקון עבור {total} המתכונים הנבחרים",
|
||||
"repairBulkFailed": "תיקון המתכונים הנבחרים נכשל: {message}",
|
||||
"rematchComplete": "הותאמו {entries} פריטים ב־{recipes} מתכונים",
|
||||
"rematchCompleteErrors": "הותאמו {entries} פריטים ב־{recipes} מתכונים, {failures} נכשלו",
|
||||
"rematchAllFailed": "ההתאמה נכשלה עבור {failures} מתוך {total} מתכונים שנבחרו",
|
||||
@@ -2248,6 +2229,7 @@
|
||||
"rematchSkipped": "אין צורך בהתאמה עבור {total} המתכונים שנבחרו",
|
||||
"rematchFailed": "ההתאמה מחדש של המתכונים שנבחרו נכשלה: {message}",
|
||||
"reimporting": "מייבא מתכון מחדש מהמקור...",
|
||||
"reimportingViaExtension": "מייבא מתכון מחדש {current}/{total} דרך תוסף הדפדפן...",
|
||||
"reimportSuccess": "המתכון יובא מחדש בהצלחה",
|
||||
"reimportBulkComplete": "ייבוא מחדש הושלם: {completed} יובאו, {failed} נכשלו (מתוך {total})",
|
||||
"reimportBulkFailed": "ייבוא מחדש של חלק מהמתכונים נכשל",
|
||||
|
||||
+1
-19
@@ -212,13 +212,6 @@
|
||||
"none": "すべての{typePlural}には既にライセンスメタデータがあります",
|
||||
"error": "{typePlural}のライセンスメタデータを更新できませんでした: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "レシピデータの修復",
|
||||
"loading": "レシピデータを修復中...",
|
||||
"success": "{count} 件のレシピを正常に修復しました。",
|
||||
"cancelled": "修復がキャンセルされました。{count}件のレシピが修復されました。",
|
||||
"error": "レシピの修復に失敗しました: {message}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "レシピをローカルモデルに再マッチング",
|
||||
"loading": "レシピをローカルモデルに再マッチングしています...",
|
||||
@@ -821,7 +814,6 @@
|
||||
"setContentRating": "すべてのモデルのコンテンツレーティングを設定",
|
||||
"copyAll": "すべての構文をコピー",
|
||||
"refreshAll": "すべてのメタデータを更新",
|
||||
"repairMetadata": "選択したレシピのメタデータを修復",
|
||||
"rematchMetadata": "選択したモデルをローカルモデルに再マッチング",
|
||||
"reimportMetadata": "ソースから再インポート",
|
||||
"checkUpdates": "選択項目の更新を確認",
|
||||
@@ -877,7 +869,6 @@
|
||||
"replacePreview": "プレビューを置換",
|
||||
"setContentRating": "コンテンツレーティングを設定",
|
||||
"moveToFolder": "フォルダに移動",
|
||||
"repairMetadata": "メタデータを修復",
|
||||
"rematchMetadata": "ローカルモデルに再マッチング",
|
||||
"reimportMetadata": "ソースから再インポート",
|
||||
"excludeModel": "モデルを除外",
|
||||
@@ -1130,13 +1121,6 @@
|
||||
"getInfoFailed": "不足LoRAの情報取得に失敗しました",
|
||||
"prepareError": "ダウンロード用LoRAの準備中にエラー：{message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "レシピのメタデータを修復中...",
|
||||
"success": "レシピのメタデータが正常に修復されました",
|
||||
"skipped": "レシピはすでに最新バージョンです。修復は不要です",
|
||||
"failed": "レシピの修復に失敗しました: {message}",
|
||||
"missingId": "レシピを修復できません: レシピIDがありません"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "ソースからレシピを再インポート中...",
|
||||
"success": "レシピの再インポートが完了しました",
|
||||
@@ -2238,9 +2222,6 @@
|
||||
"batchImportBrowseFailed": "フォルダを参照できませんでした: {message}",
|
||||
"batchImportDirectorySelected": "選択されたフォルダ: {path}",
|
||||
"noRecipesSelected": "レシピが選択されていません",
|
||||
"repairBulkComplete": "修復完了：{repaired} 件修復、{skipped} 件スキップ（合計 {total} 件）",
|
||||
"repairBulkSkipped": "選択した {total} 件のレシピは修復不要です",
|
||||
"repairBulkFailed": "選択したレシピの修復に失敗しました：{message}",
|
||||
"rematchComplete": "{recipes} 件のレシピで {entries} エントリをマッチングしました",
|
||||
"rematchCompleteErrors": "{recipes} 件のレシピで {entries} エントリをマッチングしました（{failures} 件失敗）",
|
||||
"rematchAllFailed": "選択した {total} 件中 {failures} 件のレシピの再マッチングに失敗しました",
|
||||
@@ -2248,6 +2229,7 @@
|
||||
"rematchSkipped": "選択した {total} 件のレシピは再マッチングの必要がありませんでした",
|
||||
"rematchFailed": "選択したレシピの再マッチングに失敗しました：{message}",
|
||||
"reimporting": "ソースからレシピを再インポート中...",
|
||||
"reimportingViaExtension": "ブラウザ拡張機能経由でレシピを再インポート中 ({current}/{total})...",
|
||||
"reimportSuccess": "レシピの再インポートが完了しました",
|
||||
"reimportBulkComplete": "再インポート完了：{completed} 件成功、{failed} 件失敗（合計 {total} 件）",
|
||||
"reimportBulkFailed": "一部のレシピの再インポートに失敗しました",
|
||||
|
||||
+1
-19
@@ -212,13 +212,6 @@
|
||||
"none": "모든 {typePlural}에 이미 라이선스 메타데이터가 있습니다",
|
||||
"error": "{typePlural}의 라이선스 메타데이터를 새로고침하지 못했습니다: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "레시피 데이터 복구",
|
||||
"loading": "레시피 데이터 복구 중...",
|
||||
"success": "{count}개의 레시피가 성공적으로 복구되었습니다.",
|
||||
"cancelled": "수리가 취소되었습니다. {count}개의 레시피가 수리되었습니다.",
|
||||
"error": "레시피 복구 실패: {message}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "레시피를 로컬 모델에 다시 매칭",
|
||||
"loading": "레시피를 로컬 모델에 다시 매칭하는 중...",
|
||||
@@ -821,7 +814,6 @@
|
||||
"setContentRating": "모든 모델에 콘텐츠 등급 설정",
|
||||
"copyAll": "모든 문법 복사",
|
||||
"refreshAll": "모든 메타데이터 새로고침",
|
||||
"repairMetadata": "선택한 레시피 메타데이터 복구",
|
||||
"rematchMetadata": "선택 항목을 로컬 모델에 다시 매칭",
|
||||
"reimportMetadata": "소스에서 다시 가져오기",
|
||||
"checkUpdates": "선택 항목 업데이트 확인",
|
||||
@@ -877,7 +869,6 @@
|
||||
"replacePreview": "미리보기 교체",
|
||||
"setContentRating": "콘텐츠 등급 설정",
|
||||
"moveToFolder": "폴더로 이동",
|
||||
"repairMetadata": "메타데이터 복구",
|
||||
"rematchMetadata": "로컬 모델에 다시 매칭",
|
||||
"reimportMetadata": "소스에서 다시 가져오기",
|
||||
"excludeModel": "모델 제외",
|
||||
@@ -1130,13 +1121,6 @@
|
||||
"getInfoFailed": "누락된 LoRA 정보를 가져오는데 실패했습니다",
|
||||
"prepareError": "LoRA 다운로드 준비 중 오류: {message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "레시피 메타데이터 복구 중...",
|
||||
"success": "레시피 메타데이터가 성공적으로 복구되었습니다",
|
||||
"skipped": "레시피가 이미 최신 버전입니다. 복구가 필요하지 않습니다",
|
||||
"failed": "레시피 복구 실패: {message}",
|
||||
"missingId": "레시피를 복구할 수 없음: 레시피 ID 누락"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "소스에서 레시피를 다시 가져오는 중...",
|
||||
"success": "레시피를 다시 가져왔습니다",
|
||||
@@ -2238,9 +2222,6 @@
|
||||
"batchImportBrowseFailed": "폴더를 찾아보지 못했습니다: {message}",
|
||||
"batchImportDirectorySelected": "선택한 폴더: {path}",
|
||||
"noRecipesSelected": "선택한 레시피가 없습니다",
|
||||
"repairBulkComplete": "복구 완료: {repaired}개 복구, {skipped}개 건너뜀 (총 {total}개)",
|
||||
"repairBulkSkipped": "선택한 {total}개 레시피는 복구가 필요하지 않습니다",
|
||||
"repairBulkFailed": "선택한 레시피 복구 실패: {message}",
|
||||
"rematchComplete": "{recipes}개 레시피에서 {entries}개 항목이 매칭되었습니다",
|
||||
"rematchCompleteErrors": "{recipes}개 레시피에서 {entries}개 항목이 매칭되었습니다. {failures}개 실패",
|
||||
"rematchAllFailed": "선택한 {total}개 레시피 중 {failures}개 재매칭 실패",
|
||||
@@ -2248,6 +2229,7 @@
|
||||
"rematchSkipped": "선택한 {total}개 레시피는 재매칭이 필요하지 않습니다",
|
||||
"rematchFailed": "선택한 레시피 재매칭 실패: {message}",
|
||||
"reimporting": "소스에서 레시피를 다시 가져오는 중...",
|
||||
"reimportingViaExtension": "브라우저 확장 프로그램을 통해 레시피를 다시 가져오는 중 ({current}/{total})...",
|
||||
"reimportSuccess": "레시피를 다시 가져왔습니다",
|
||||
"reimportBulkComplete": "다시 가져오기 완료: {completed}개 성공, {failed}개 실패 (총 {total}개)",
|
||||
"reimportBulkFailed": "일부 레시피를 다시 가져오지 못했습니다",
|
||||
|
||||
+1
-19
@@ -212,13 +212,6 @@
|
||||
"none": "У всех {typePlural} уже есть метаданные лицензии",
|
||||
"error": "Не удалось обновить метаданные лицензии для {typePlural}: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "Восстановить данные рецептов",
|
||||
"loading": "Восстановление данных рецептов...",
|
||||
"success": "Успешно восстановлено {count} рецептов.",
|
||||
"cancelled": "Восстановление отменено. {count} рецептов было восстановлено.",
|
||||
"error": "Ошибка восстановления рецептов: {message}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "Повторное сопоставление рецептов с локальными моделями",
|
||||
"loading": "Повторное сопоставление рецептов с локальными моделями...",
|
||||
@@ -821,7 +814,6 @@
|
||||
"setContentRating": "Установить рейтинг контента для всех",
|
||||
"copyAll": "Копировать весь синтаксис",
|
||||
"refreshAll": "Обновить все метаданные",
|
||||
"repairMetadata": "Восстановить метаданные для выбранных",
|
||||
"rematchMetadata": "Сопоставить выбранные с локальными моделями",
|
||||
"reimportMetadata": "Переимпортировать из источника",
|
||||
"checkUpdates": "Проверить обновления для выбранных",
|
||||
@@ -877,7 +869,6 @@
|
||||
"replacePreview": "Заменить превью",
|
||||
"setContentRating": "Установить рейтинг контента",
|
||||
"moveToFolder": "Переместить в папку",
|
||||
"repairMetadata": "Восстановить метаданные",
|
||||
"rematchMetadata": "Сопоставить с локальными моделями",
|
||||
"reimportMetadata": "Переимпортировать из источника",
|
||||
"excludeModel": "Исключить модель",
|
||||
@@ -1130,13 +1121,6 @@
|
||||
"getInfoFailed": "Не удалось получить информацию для отсутствующих LoRAs",
|
||||
"prepareError": "Ошибка подготовки LoRAs для загрузки: {message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "Восстановление метаданных рецепта...",
|
||||
"success": "Метаданные рецепта успешно восстановлены",
|
||||
"skipped": "Рецепт уже последней версии, восстановление не требуется",
|
||||
"failed": "Не удалось восстановить рецепт: {message}",
|
||||
"missingId": "Не удалось восстановить рецепт: отсутствует ID рецепта"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "Переимпорт рецепта из источника...",
|
||||
"success": "Рецепт успешно переимпортирован",
|
||||
@@ -2238,9 +2222,6 @@
|
||||
"batchImportBrowseFailed": "Не удалось открыть папку: {message}",
|
||||
"batchImportDirectorySelected": "Выбрана папка: {path}",
|
||||
"noRecipesSelected": "Рецепты не выбраны",
|
||||
"repairBulkComplete": "Восстановление завершено: {repaired} восстановлено, {skipped} пропущено (из {total})",
|
||||
"repairBulkSkipped": "Ни один из {total} выбранных рецептов не требует восстановления",
|
||||
"repairBulkFailed": "Не удалось восстановить выбранные рецепты: {message}",
|
||||
"rematchComplete": "Сопоставлено записей: {entries} в рецептах: {recipes}",
|
||||
"rematchCompleteErrors": "Сопоставлено записей: {entries} в рецептах: {recipes}, ошибок: {failures}",
|
||||
"rematchAllFailed": "Не удалось сопоставить: {failures} из {total} выбранных рецептов",
|
||||
@@ -2248,6 +2229,7 @@
|
||||
"rematchSkipped": "Ни один из {total} выбранных рецептов не требует сопоставления",
|
||||
"rematchFailed": "Не удалось сопоставить выбранные рецепты: {message}",
|
||||
"reimporting": "Переимпорт рецепта из источника...",
|
||||
"reimportingViaExtension": "Переимпорт рецепта {current}/{total} через расширение браузера...",
|
||||
"reimportSuccess": "Рецепт успешно переимпортирован",
|
||||
"reimportBulkComplete": "Переимпорт завершён: {completed} переимпортировано, {failed} ошибок (из {total})",
|
||||
"reimportBulkFailed": "Не удалось переимпортировать некоторые рецепты",
|
||||
|
||||
+1
-19
@@ -212,13 +212,6 @@
|
||||
"none": "所有 {typePlural} 都已具备许可证元数据",
|
||||
"error": "刷新 {typePlural} 的许可证元数据失败：{message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "修复配方数据",
|
||||
"loading": "正在修复配方数据...",
|
||||
"success": "成功修复了 {count} 个配方。",
|
||||
"cancelled": "修复已取消。已修复 {count} 个配方。",
|
||||
"error": "配方修复失败：{message}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "将配方重新匹配到本地模型",
|
||||
"loading": "正在将配方重新匹配到本地模型...",
|
||||
@@ -821,7 +814,6 @@
|
||||
"setContentRating": "为所选中设置内容评级",
|
||||
"copyAll": "复制所选中语法",
|
||||
"refreshAll": "刷新所选中元数据",
|
||||
"repairMetadata": "修复所选中元数据",
|
||||
"rematchMetadata": "将所选中重新匹配到本地模型",
|
||||
"reimportMetadata": "从源重新导入",
|
||||
"checkUpdates": "检查所选更新",
|
||||
@@ -877,7 +869,6 @@
|
||||
"replacePreview": "替换预览",
|
||||
"setContentRating": "设置内容评级",
|
||||
"moveToFolder": "移动到文件夹",
|
||||
"repairMetadata": "修复元数据",
|
||||
"rematchMetadata": "重新匹配到本地模型",
|
||||
"reimportMetadata": "从源重新导入",
|
||||
"excludeModel": "排除模型",
|
||||
@@ -1130,13 +1121,6 @@
|
||||
"getInfoFailed": "获取缺失 LoRA 信息失败",
|
||||
"prepareError": "准备下载 LoRA 时出错：{message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "正在修复配方元数据...",
|
||||
"success": "配方元数据修复成功",
|
||||
"skipped": "配方已是最新版本，无需修复",
|
||||
"failed": "修复配方失败：{message}",
|
||||
"missingId": "无法修复配方：缺少配方 ID"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "正在从源重新导入配方...",
|
||||
"success": "配方已从源重新导入成功",
|
||||
@@ -2238,9 +2222,6 @@
|
||||
"batchImportBrowseFailed": "浏览目录失败：{message}",
|
||||
"batchImportDirectorySelected": "已选择目录：{path}",
|
||||
"noRecipesSelected": "未选择任何配方",
|
||||
"repairBulkComplete": "修复完成：{repaired} 个已修复，{skipped} 个已跳过（共 {total} 个）",
|
||||
"repairBulkSkipped": "所选 {total} 个配方无需修复",
|
||||
"repairBulkFailed": "修复所选配方失败：{message}",
|
||||
"rematchComplete": "已匹配 {entries} 个条目，涉及 {recipes} 个配方",
|
||||
"rematchCompleteErrors": "已匹配 {entries} 个条目，涉及 {recipes} 个配方，{failures} 个失败",
|
||||
"rematchAllFailed": "{failures}/{total} 个所选配方重新匹配失败",
|
||||
@@ -2248,6 +2229,7 @@
|
||||
"rematchSkipped": "{total} 个所选配方均无需重新匹配",
|
||||
"rematchFailed": "重新匹配所选配方失败：{message}",
|
||||
"reimporting": "正在从源重新导入配方...",
|
||||
"reimportingViaExtension": "正在通过浏览器扩展重新导入配方 {current}/{total}...",
|
||||
"reimportSuccess": "配方已从源重新导入成功",
|
||||
"reimportBulkComplete": "重新导入完成：{completed} 个已导入，{failed} 个失败（共 {total} 个）",
|
||||
"reimportBulkFailed": "重新导入某些配方失败",
|
||||
|
||||
+1
-19
@@ -212,13 +212,6 @@
|
||||
"none": "所有 {typePlural} 已具備授權中繼資料",
|
||||
"error": "重新整理 {typePlural} 授權中繼資料失敗：{message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "修復配方資料",
|
||||
"loading": "正在修復配方資料...",
|
||||
"success": "成功修復 {count} 個配方。",
|
||||
"cancelled": "修復已取消。已修復 {count} 個配方。",
|
||||
"error": "配方修復失敗：{message}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "將配方重新匹配到本地模型",
|
||||
"loading": "正在將配方重新匹配到本地模型...",
|
||||
@@ -821,7 +814,6 @@
|
||||
"setContentRating": "為全部設定內容分級",
|
||||
"copyAll": "複製全部語法",
|
||||
"refreshAll": "刷新全部 metadata",
|
||||
"repairMetadata": "修復所選中元數據",
|
||||
"rematchMetadata": "將所選中重新匹配到本地模型",
|
||||
"reimportMetadata": "從來源重新匯入",
|
||||
"checkUpdates": "檢查所選更新",
|
||||
@@ -877,7 +869,6 @@
|
||||
"replacePreview": "更換預覽圖",
|
||||
"setContentRating": "設定內容分級",
|
||||
"moveToFolder": "移動到資料夾",
|
||||
"repairMetadata": "修復元數據",
|
||||
"rematchMetadata": "重新匹配到本地模型",
|
||||
"reimportMetadata": "從來源重新匯入",
|
||||
"excludeModel": "排除模型",
|
||||
@@ -1130,13 +1121,6 @@
|
||||
"getInfoFailed": "取得缺少 LoRA 資訊失敗",
|
||||
"prepareError": "準備下載 LoRA 時發生錯誤：{message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "正在修復配方元數據...",
|
||||
"success": "配方元數據修復成功",
|
||||
"skipped": "配方已是最新版本，無需修復",
|
||||
"failed": "修復配方失敗：{message}",
|
||||
"missingId": "無法修復配方：缺少配方 ID"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "正在從來源重新匯入配方...",
|
||||
"success": "配方已從來源重新匯入成功",
|
||||
@@ -2238,9 +2222,6 @@
|
||||
"batchImportBrowseFailed": "瀏覽目錄失敗：{message}",
|
||||
"batchImportDirectorySelected": "已選擇目錄：{path}",
|
||||
"noRecipesSelected": "未選取任何配方",
|
||||
"repairBulkComplete": "修復完成：{repaired} 個已修復，{skipped} 個已跳過（共 {total} 個）",
|
||||
"repairBulkSkipped": "所選 {total} 個配方無需修復",
|
||||
"repairBulkFailed": "修復所選配方失敗：{message}",
|
||||
"rematchComplete": "已匹配 {entries} 個條目，涉及 {recipes} 個配方",
|
||||
"rematchCompleteErrors": "已匹配 {entries} 個條目，涉及 {recipes} 個配方，{failures} 個失敗",
|
||||
"rematchAllFailed": "{failures}/{total} 個所選配方重新匹配失敗",
|
||||
@@ -2248,6 +2229,7 @@
|
||||
"rematchSkipped": "{total} 個所選配方均無需重新匹配",
|
||||
"rematchFailed": "重新匹配所選配方失敗：{message}",
|
||||
"reimporting": "正在從來源重新匯入配方...",
|
||||
"reimportingViaExtension": "正在透過瀏覽器擴充功能重新匯入配方 {current}/{total}...",
|
||||
"reimportSuccess": "配方已從來源重新匯入成功",
|
||||
"reimportBulkComplete": "重新匯入完成：{completed} 個已匯入，{failed} 個失敗（共 {total} 個）",
|
||||
"reimportBulkFailed": "重新匯入某些配方失敗",
|
||||
|
||||
@@ -129,11 +129,6 @@ class RecipeHandlerSet:
|
||||
"get_recipes_for_checkpoint": self.query.get_recipes_for_checkpoint,
|
||||
"scan_recipes": self.query.scan_recipes,
|
||||
"move_recipe": self.management.move_recipe,
|
||||
"repair_recipes": self.management.repair_recipes,
|
||||
"cancel_repair": self.management.cancel_repair,
|
||||
"repair_recipe": self.management.repair_recipe,
|
||||
"repair_recipes_bulk": self.management.repair_recipes_bulk,
|
||||
"get_repair_progress": self.management.get_repair_progress,
|
||||
"rematch_recipes": self.management.rematch_recipes,
|
||||
"cancel_rematch": self.management.cancel_rematch,
|
||||
"rematch_recipe": self.management.rematch_recipe,
|
||||
@@ -796,157 +791,6 @@ class RecipeManagementHandler:
|
||||
self._logger.error("Error saving recipe: %s", exc, exc_info=True)
|
||||
return web.json_response({"error": str(exc)}, status=500)
|
||||
|
||||
async def repair_recipes(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
return web.json_response(
|
||||
{"success": False, "error": "Recipe scanner unavailable"},
|
||||
status=503,
|
||||
)
|
||||
|
||||
# Check if already running
|
||||
if self._ws_manager.is_recipe_repair_running():
|
||||
return web.json_response(
|
||||
{"success": False, "error": "Recipe repair already in progress"},
|
||||
status=409,
|
||||
)
|
||||
|
||||
recipe_scanner.reset_cancellation()
|
||||
|
||||
async def progress_callback(data):
|
||||
await self._ws_manager.broadcast_recipe_repair_progress(data)
|
||||
|
||||
# Run in background to avoid timeout
|
||||
async def run_repair():
|
||||
try:
|
||||
await recipe_scanner.repair_all_recipes(
|
||||
progress_callback=progress_callback
|
||||
)
|
||||
except Exception as e:
|
||||
self._logger.error(
|
||||
f"Error in recipe repair task: {e}", exc_info=True
|
||||
)
|
||||
await self._ws_manager.broadcast_recipe_repair_progress(
|
||||
{"status": "error", "error": str(e)}
|
||||
)
|
||||
finally:
|
||||
# Keep the final status for a while so the UI can see it
|
||||
await asyncio.sleep(5)
|
||||
# Don't cleanup if it was cancelled, let the UI see the cancelled state for a bit?
|
||||
# Actually cleanup_recipe_repair_progress is fine as long as we waited enough.
|
||||
self._ws_manager.cleanup_recipe_repair_progress()
|
||||
|
||||
asyncio.create_task(run_repair())
|
||||
|
||||
return web.json_response(
|
||||
{"success": True, "message": "Recipe repair started"}
|
||||
)
|
||||
except Exception as exc:
|
||||
self._logger.error("Error starting recipe repair: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def cancel_repair(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
return web.json_response(
|
||||
{"success": False, "error": "Recipe scanner unavailable"},
|
||||
status=503,
|
||||
)
|
||||
|
||||
recipe_scanner.cancel_task()
|
||||
return web.json_response(
|
||||
{"success": True, "message": "Cancellation requested"}
|
||||
)
|
||||
except Exception as exc:
|
||||
self._logger.error("Error cancelling recipe repair: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def repair_recipes_bulk(self, request: web.Request) -> web.Response:
|
||||
"""Bulk repair metadata for multiple recipes by their IDs.
|
||||
|
||||
Accepts a JSON body with a "recipe_ids" array and iterates
|
||||
repair_recipe_by_id over each entry, collecting statistics.
|
||||
"""
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
return web.json_response(
|
||||
{"success": False, "error": "Recipe scanner unavailable"},
|
||||
status=503,
|
||||
)
|
||||
|
||||
data = await request.json()
|
||||
recipe_ids = data.get("recipe_ids", [])
|
||||
if not recipe_ids:
|
||||
return web.json_response(
|
||||
{"success": False, "error": "recipe_ids are required"},
|
||||
status=400,
|
||||
)
|
||||
|
||||
total = len(recipe_ids)
|
||||
repaired = 0
|
||||
skipped = 0
|
||||
errors = 0
|
||||
recipes = []
|
||||
|
||||
for recipe_id in recipe_ids:
|
||||
try:
|
||||
result = await recipe_scanner.repair_recipe_by_id(recipe_id)
|
||||
if result.get("success"):
|
||||
repaired += result.get("repaired", 0)
|
||||
skipped += result.get("skipped", 0)
|
||||
if result.get("recipe"):
|
||||
recipes.append(result["recipe"])
|
||||
else:
|
||||
errors += 1
|
||||
except RecipeNotFoundError:
|
||||
skipped += 1
|
||||
except Exception as exc:
|
||||
self._logger.error(
|
||||
"Error repairing recipe %s: %s", recipe_id, exc
|
||||
)
|
||||
errors += 1
|
||||
|
||||
return web.json_response({
|
||||
"success": True,
|
||||
"total": total,
|
||||
"repaired": repaired,
|
||||
"skipped": skipped,
|
||||
"errors": errors,
|
||||
"recipes": recipes,
|
||||
})
|
||||
except Exception as exc:
|
||||
self._logger.error(
|
||||
"Error performing bulk repair: %s", exc, exc_info=True
|
||||
)
|
||||
return web.json_response(
|
||||
{"success": False, "error": str(exc)}, status=500
|
||||
)
|
||||
|
||||
async def repair_recipe(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
return web.json_response(
|
||||
{"success": False, "error": "Recipe scanner unavailable"},
|
||||
status=503,
|
||||
)
|
||||
|
||||
recipe_id = request.match_info["recipe_id"]
|
||||
result = await recipe_scanner.repair_recipe_by_id(recipe_id)
|
||||
return web.json_response(result)
|
||||
except RecipeNotFoundError as exc:
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=404)
|
||||
except Exception as exc:
|
||||
self._logger.error("Error repairing single recipe: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def rematch_recipes(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
@@ -958,12 +802,9 @@ class RecipeManagementHandler:
|
||||
)
|
||||
|
||||
# Mutual exclusion: a global rematch cannot start while a rematch
|
||||
# OR a repair is already running — both mutate recipes under the
|
||||
# same mutation lock.
|
||||
if (
|
||||
self._ws_manager.is_recipe_rematch_running()
|
||||
or self._ws_manager.is_recipe_repair_running()
|
||||
):
|
||||
# is already running — both mutate recipes under the same
|
||||
# mutation lock.
|
||||
if self._ws_manager.is_recipe_rematch_running():
|
||||
return web.json_response(
|
||||
{"success": False, "error": "Recipe rematch already in progress"},
|
||||
status=409,
|
||||
@@ -1179,12 +1020,55 @@ class RecipeManagementHandler:
|
||||
persisted_source_path=persisted_source_path,
|
||||
)
|
||||
|
||||
async with self._import_semaphore:
|
||||
import_response = await self._do_import_from_url(
|
||||
source_path,
|
||||
recipe_scanner,
|
||||
target_dir=old_folder,
|
||||
)
|
||||
# Optional caller-supplied metadata payload (companion browser
|
||||
# extension re-import). Only honored for CivitAI image page
|
||||
# sources; everything else uses the native URL import below.
|
||||
params = request.rel_url.query
|
||||
payload_image_url = params.get("image_url")
|
||||
payload_name = params.get("name")
|
||||
payload_resources = params.get("resources")
|
||||
has_import_payload = bool(
|
||||
payload_image_url and payload_name and payload_resources
|
||||
)
|
||||
|
||||
import_response: web.Response | None = None
|
||||
if has_import_payload and image_id:
|
||||
try:
|
||||
async with self._import_semaphore:
|
||||
import_response = await self._import_remote_recipe_impl(
|
||||
image_url=payload_image_url,
|
||||
name=payload_name,
|
||||
resources_raw=payload_resources,
|
||||
gen_params_raw=params.get("gen_params"),
|
||||
tags_raw=params.get("tags"),
|
||||
base_model=params.get("base_model", "") or "",
|
||||
source_path=source_path,
|
||||
target_dir=old_folder,
|
||||
)
|
||||
except RecipeValidationError as exc:
|
||||
# Malformed resources/gen_params JSON: treat as "no
|
||||
# payload" and use the legacy URL re-import.
|
||||
self._logger.warning(
|
||||
"Ignoring malformed re-import payload for recipe %s "
|
||||
"(%s); falling back to source URL re-import",
|
||||
recipe_id,
|
||||
exc,
|
||||
)
|
||||
except Exception as exc:
|
||||
self._logger.warning(
|
||||
"Payload-based re-import failed for recipe %s: %s; "
|
||||
"falling back to source URL re-import",
|
||||
recipe_id,
|
||||
exc,
|
||||
)
|
||||
|
||||
if import_response is None:
|
||||
async with self._import_semaphore:
|
||||
import_response = await self._do_import_from_url(
|
||||
source_path,
|
||||
recipe_scanner,
|
||||
target_dir=old_folder,
|
||||
)
|
||||
|
||||
await self._persistence_service.delete_recipe(
|
||||
recipe_scanner=recipe_scanner, recipe_id=recipe_id
|
||||
@@ -1211,14 +1095,19 @@ class RecipeManagementHandler:
|
||||
exc,
|
||||
)
|
||||
|
||||
return web.json_response(
|
||||
{
|
||||
"success": True,
|
||||
"old_recipe_id": recipe_id,
|
||||
"recipe_id": new_recipe_id,
|
||||
"source_path": source_path,
|
||||
}
|
||||
response_body: Dict[str, Any] = {
|
||||
"success": True,
|
||||
"old_recipe_id": recipe_id,
|
||||
"recipe_id": new_recipe_id,
|
||||
"source_path": source_path,
|
||||
}
|
||||
loras_count = await self._count_recipe_loras(
|
||||
recipe_scanner, new_recipe_id
|
||||
)
|
||||
if loras_count is not None:
|
||||
response_body["loras_count"] = loras_count
|
||||
|
||||
return web.json_response(response_body)
|
||||
except RecipeNotFoundError as exc:
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=404)
|
||||
except RecipeValidationError as exc:
|
||||
@@ -1231,18 +1120,6 @@ class RecipeManagementHandler:
|
||||
)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def get_repair_progress(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
progress = self._ws_manager.get_recipe_repair_progress()
|
||||
if progress:
|
||||
return web.json_response({"success": True, "progress": progress})
|
||||
return web.json_response(
|
||||
{"success": False, "message": "No repair in progress"}, status=404
|
||||
)
|
||||
except Exception as exc:
|
||||
self._logger.error("Error getting repair progress: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def import_remote_recipe(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
@@ -1263,31 +1140,14 @@ class RecipeManagementHandler:
|
||||
if not resources_raw:
|
||||
raise RecipeValidationError("Missing required field: resources")
|
||||
|
||||
checkpoint_entry, lora_entries = self._parse_resources_payload(
|
||||
resources_raw
|
||||
)
|
||||
gen_params_request = self._parse_gen_params(params.get("gen_params"))
|
||||
|
||||
self._logger.info(
|
||||
"Remote recipe import received: url=%s, lora_count=%d",
|
||||
image_url,
|
||||
len(lora_entries),
|
||||
)
|
||||
self._logger.debug(
|
||||
" gen_params_keys=%s, checkpoint_keys=%s",
|
||||
sorted(gen_params_request.keys()) if gen_params_request else [],
|
||||
sorted(checkpoint_entry.keys()) if isinstance(checkpoint_entry, dict) else [],
|
||||
)
|
||||
|
||||
# Throttle concurrent imports to avoid starving ComfyUI's event loop
|
||||
async with self._import_semaphore:
|
||||
return await self._do_import_remote_recipe(
|
||||
return await self._import_remote_recipe_impl(
|
||||
image_url=image_url,
|
||||
name=name,
|
||||
lora_entries=lora_entries,
|
||||
checkpoint_entry=checkpoint_entry,
|
||||
gen_params_request=gen_params_request,
|
||||
tags=self._parse_tags(params.get("tags")),
|
||||
resources_raw=resources_raw,
|
||||
gen_params_raw=params.get("gen_params"),
|
||||
tags_raw=params.get("tags"),
|
||||
base_model=params.get("base_model", "") or "",
|
||||
source_path=params.get("source_path") or image_url,
|
||||
)
|
||||
@@ -1301,6 +1161,52 @@ class RecipeManagementHandler:
|
||||
)
|
||||
return web.json_response({"error": str(exc)}, status=500)
|
||||
|
||||
async def _import_remote_recipe_impl(
|
||||
self,
|
||||
*,
|
||||
image_url: str,
|
||||
name: str,
|
||||
resources_raw: str,
|
||||
gen_params_raw: Optional[str],
|
||||
tags_raw: Optional[str],
|
||||
base_model: str,
|
||||
source_path: str,
|
||||
target_dir: str | None = None,
|
||||
) -> web.Response:
|
||||
"""Payload-based remote import engine shared by import-remote and the
|
||||
extension-driven re-import path.
|
||||
|
||||
Parses the caller-supplied payloads and delegates to
|
||||
:meth:`_do_import_remote_recipe`. Raises ``RecipeValidationError`` on
|
||||
malformed payloads so callers can decide how to handle them (the
|
||||
re-import path falls back to the legacy URL import).
|
||||
"""
|
||||
checkpoint_entry, lora_entries = self._parse_resources_payload(resources_raw)
|
||||
gen_params_request = self._parse_gen_params(gen_params_raw)
|
||||
|
||||
self._logger.info(
|
||||
"Remote recipe import received: url=%s, lora_count=%d",
|
||||
image_url,
|
||||
len(lora_entries),
|
||||
)
|
||||
self._logger.debug(
|
||||
" gen_params_keys=%s, checkpoint_keys=%s",
|
||||
sorted(gen_params_request.keys()) if gen_params_request else [],
|
||||
sorted(checkpoint_entry.keys()) if isinstance(checkpoint_entry, dict) else [],
|
||||
)
|
||||
|
||||
return await self._do_import_remote_recipe(
|
||||
image_url=image_url,
|
||||
name=name,
|
||||
lora_entries=lora_entries,
|
||||
checkpoint_entry=checkpoint_entry,
|
||||
gen_params_request=gen_params_request,
|
||||
tags=self._parse_tags(tags_raw),
|
||||
base_model=base_model,
|
||||
source_path=source_path,
|
||||
target_dir=target_dir,
|
||||
)
|
||||
|
||||
async def _do_import_remote_recipe(
|
||||
self,
|
||||
*,
|
||||
@@ -1312,6 +1218,7 @@ class RecipeManagementHandler:
|
||||
tags: list[Any],
|
||||
base_model: str,
|
||||
source_path: str,
|
||||
target_dir: str | None = None,
|
||||
) -> web.Response:
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
@@ -1475,6 +1382,7 @@ class RecipeManagementHandler:
|
||||
tags=tags,
|
||||
metadata=metadata,
|
||||
extension=extension,
|
||||
target_dir=target_dir,
|
||||
)
|
||||
return web.json_response(result.payload, status=result.status)
|
||||
|
||||
@@ -1939,6 +1847,25 @@ class RecipeManagementHandler:
|
||||
return []
|
||||
return [tag.strip() for tag in tag_text.split(",") if tag.strip()]
|
||||
|
||||
async def _count_recipe_loras(
|
||||
self, recipe_scanner: Any, recipe_id: Optional[str]
|
||||
) -> Optional[int]:
|
||||
"""Best-effort LoRA count for a freshly saved recipe (for the
|
||||
re-import response). Returns None when the recipe cannot be read."""
|
||||
if not recipe_id:
|
||||
return None
|
||||
try:
|
||||
recipe = await recipe_scanner.get_recipe_by_id(recipe_id)
|
||||
except Exception as exc:
|
||||
self._logger.debug(
|
||||
"Could not read new recipe %s for loras_count: %s",
|
||||
recipe_id,
|
||||
exc,
|
||||
)
|
||||
return None
|
||||
loras = (recipe or {}).get("loras")
|
||||
return len(loras) if isinstance(loras, list) else None
|
||||
|
||||
def _parse_gen_params(self, payload: Optional[str]) -> Optional[Dict[str, Any]]:
|
||||
if payload is None:
|
||||
return None
|
||||
|
||||
@@ -84,11 +84,6 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
|
||||
"GET", "/api/lm/recipes/for-checkpoint", "get_recipes_for_checkpoint"
|
||||
),
|
||||
RouteDefinition("GET", "/api/lm/recipes/scan", "scan_recipes"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/repair", "repair_recipes"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/cancel-repair", "cancel_repair"),
|
||||
RouteDefinition("POST", "/api/lm/recipe/{recipe_id}/repair", "repair_recipe"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/repair-bulk", "repair_recipes_bulk"),
|
||||
RouteDefinition("GET", "/api/lm/recipes/repair-progress", "get_repair_progress"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/rematch", "rematch_recipes"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/rematch-bulk", "rematch_recipes_bulk"),
|
||||
RouteDefinition("POST", "/api/lm/recipe/{recipe_id}/rematch", "rematch_recipe"),
|
||||
@@ -115,6 +110,11 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
|
||||
RouteDefinition(
|
||||
"POST", "/api/lm/recipe/{recipe_id}/reimport", "reimport_recipe"
|
||||
),
|
||||
# The companion browser extension only ever issues GET requests, so the
|
||||
# payload-based re-import variant must also be reachable via GET.
|
||||
RouteDefinition(
|
||||
"GET", "/api/lm/recipe/{recipe_id}/reimport", "reimport_recipe"
|
||||
),
|
||||
RouteDefinition(
|
||||
"POST", "/api/lm/recipe/{recipe_id}/send-workflow", "send_recipe_workflow"
|
||||
),
|
||||
|
||||
@@ -505,6 +505,50 @@ class CivitaiClient:
|
||||
logger.warning(f"Failed to fetch version by id {version_id}")
|
||||
return None
|
||||
|
||||
async def get_version_file_mini(
|
||||
self, version_id: int, file_id: int
|
||||
) -> Optional[Dict[str, Any]]:
|
||||
"""Fetch raw stored file info via the model-versions/mini endpoint.
|
||||
|
||||
The public REST API rewrites ``files[].name`` to
|
||||
``"{model}_{version}"`` for non-LoRA model types, so every
|
||||
precision variant of a multi-file version shares one name (#1100).
|
||||
The mini endpoint returns the raw ``ModelFile.name`` in
|
||||
``fileName``. ``file_id`` is mandatory: without it mini picks a
|
||||
file via its own primary-file logic, which can disagree with the
|
||||
REST ``primary`` flag.
|
||||
|
||||
Returns the mini payload dict on success, None on any failure.
|
||||
"""
|
||||
try:
|
||||
success, data = await self._make_request(
|
||||
"GET",
|
||||
f"{self.base_url}/model-versions/mini/{version_id}",
|
||||
params={"modelFileId": file_id},
|
||||
use_auth=True,
|
||||
)
|
||||
if success and isinstance(data, dict):
|
||||
return data
|
||||
if is_expected_offline_error(data):
|
||||
return None
|
||||
logger.debug(
|
||||
"Mini endpoint lookup failed for version %s file %s: %s",
|
||||
version_id,
|
||||
file_id,
|
||||
data,
|
||||
)
|
||||
return None
|
||||
except RateLimitError:
|
||||
raise
|
||||
except Exception as exc:
|
||||
logger.debug(
|
||||
"Error fetching mini info for version %s file %s: %s",
|
||||
version_id,
|
||||
file_id,
|
||||
exc,
|
||||
)
|
||||
return None
|
||||
|
||||
async def _fetch_version_by_hash(self, model_hash: Optional[str]) -> Optional[Dict[str, Any]]:
|
||||
if not model_hash:
|
||||
return None
|
||||
|
||||
@@ -35,6 +35,7 @@ from .service_registry import ServiceRegistry
|
||||
from .settings_manager import get_settings_manager
|
||||
from .metadata_service import get_default_metadata_provider, get_metadata_provider
|
||||
from .downloader import get_downloader, DownloadProgress, DownloadStreamControl
|
||||
from .errors import RateLimitError
|
||||
from .aria2_downloader import Aria2Error, get_aria2_downloader
|
||||
from .aria2_transfer_state import Aria2TransferStateStore
|
||||
from .download_queue_service import DownloadQueueService
|
||||
@@ -929,6 +930,42 @@ class DownloadManager:
|
||||
|
||||
return download_urls
|
||||
|
||||
async def _fetch_raw_file_name(
|
||||
self,
|
||||
metadata_provider,
|
||||
version_id: Optional[int],
|
||||
file_id: Any,
|
||||
) -> Optional[str]:
|
||||
"""Best-effort lookup of the raw stored filename via the CivitAI
|
||||
model-versions/mini endpoint (#1100). Returns None on any failure so
|
||||
the caller can fall back to the (possibly rewritten) REST name."""
|
||||
if version_id is None or file_id is None:
|
||||
return None
|
||||
fetch = getattr(metadata_provider, "get_version_file_mini", None)
|
||||
if fetch is None:
|
||||
return None
|
||||
try:
|
||||
mini_info = await fetch(int(version_id), int(file_id))
|
||||
except (TypeError, ValueError):
|
||||
return None
|
||||
except RateLimitError:
|
||||
raise
|
||||
except Exception as exc:
|
||||
logger.debug(
|
||||
"Mini endpoint lookup failed for version %s file %s: %s",
|
||||
version_id,
|
||||
file_id,
|
||||
exc,
|
||||
)
|
||||
return None
|
||||
if not isinstance(mini_info, dict):
|
||||
return None
|
||||
raw_name = mini_info.get("fileName")
|
||||
if not isinstance(raw_name, str) or not raw_name.strip():
|
||||
return None
|
||||
# Defensive: never let a path component slip into the filename.
|
||||
return os.path.basename(raw_name.strip()) or None
|
||||
|
||||
def _build_metadata_for_resume(
|
||||
self,
|
||||
*,
|
||||
@@ -1858,6 +1895,24 @@ class DownloadManager:
|
||||
if not download_urls:
|
||||
return {"success": False, "error": "No mirror URL found"}
|
||||
|
||||
# The public REST API rewrites files[].name to
|
||||
# "{model}_{version}" for non-LoRA model types, so every
|
||||
# precision variant of a multi-file version shares one name and
|
||||
# lands on disk with a random short-hash suffix. The mini
|
||||
# endpoint returns the raw stored filename (#1100). CivArchive
|
||||
# already serves raw names.
|
||||
if source != "civarchive":
|
||||
raw_file_name = await self._fetch_raw_file_name(
|
||||
metadata_provider, resolved_version_id, file_info.get("id")
|
||||
)
|
||||
if raw_file_name and raw_file_name != file_info.get("name"):
|
||||
logger.info(
|
||||
"[download] Using raw stored filename '%s' instead of REST name '%s'",
|
||||
raw_file_name,
|
||||
file_info.get("name"),
|
||||
)
|
||||
file_info = {**file_info, "name": raw_file_name}
|
||||
|
||||
# 3. Prepare download
|
||||
file_name = file_info.get("name", "")
|
||||
if not file_name:
|
||||
|
||||
@@ -58,7 +58,7 @@ async def _load_model_catalog() -> Dict[str, List[str]]:
|
||||
logger.warning("Model catalog returned HTTP %s", resp.status)
|
||||
return _catalog_cache or {}
|
||||
data = await resp.json()
|
||||
except (aiohttp.ClientError, asyncio.TimeoutError, json.JSONDecodeError) as exc:
|
||||
except (aiohttp.ClientError, asyncio.TimeoutError, json.JSONDecodeError, UnicodeDecodeError) as exc:
|
||||
logger.warning("Failed to fetch model catalog: %s", exc)
|
||||
return _catalog_cache or {}
|
||||
|
||||
@@ -131,7 +131,7 @@ async def fetch_ollama_models(api_base: str) -> List[str]:
|
||||
logger.debug("Ollama API returned HTTP %s from %s", resp.status, api_base)
|
||||
return []
|
||||
data = await resp.json()
|
||||
except (aiohttp.ClientError, asyncio.TimeoutError, json.JSONDecodeError) as exc:
|
||||
except (aiohttp.ClientError, asyncio.TimeoutError, json.JSONDecodeError, UnicodeDecodeError) as exc:
|
||||
logger.debug("Ollama not reachable at %s: %s", api_base, exc)
|
||||
return []
|
||||
|
||||
|
||||
@@ -169,6 +169,17 @@ class ModelMetadataProvider(ABC):
|
||||
"""Published model count for the user; None when unsupported."""
|
||||
return None
|
||||
|
||||
async def get_version_file_mini(
|
||||
self, version_id: int, file_id: int
|
||||
) -> Optional[Dict[str, Any]]:
|
||||
"""Fetch raw stored file info via CivitAI's model-versions/mini endpoint.
|
||||
|
||||
Only the CivitAI provider implements this (#1100); other providers
|
||||
already serve raw file names (CivArchive) or cannot resolve this
|
||||
lookup (SQLite), so the default is None.
|
||||
"""
|
||||
return None
|
||||
|
||||
class CivitaiModelMetadataProvider(ModelMetadataProvider):
|
||||
"""Provider that uses Civitai API for metadata"""
|
||||
|
||||
@@ -203,6 +214,11 @@ class CivitaiModelMetadataProvider(ModelMetadataProvider):
|
||||
async def get_creator_model_count(self, username: str) -> Optional[int]:
|
||||
return await self.client.get_creator_model_count(username)
|
||||
|
||||
async def get_version_file_mini(
|
||||
self, version_id: int, file_id: int
|
||||
) -> Optional[Dict[str, Any]]:
|
||||
return await self.client.get_version_file_mini(version_id, file_id)
|
||||
|
||||
class CivArchiveModelMetadataProvider(ModelMetadataProvider):
|
||||
"""Provider that uses CivArchive API for metadata"""
|
||||
|
||||
@@ -700,6 +716,37 @@ class FallbackMetadataProvider(ModelMetadataProvider):
|
||||
continue
|
||||
return None
|
||||
|
||||
async def get_version_file_mini(
|
||||
self, version_id: int, file_id: int
|
||||
) -> Optional[Dict[str, Any]]:
|
||||
rate_limited = False
|
||||
for provider, label in self._iter_providers():
|
||||
if rate_limited and label not in _LOCAL_PROVIDER_LABELS:
|
||||
continue
|
||||
try:
|
||||
result = await self._call_with_rate_limit(
|
||||
label,
|
||||
provider.get_version_file_mini,
|
||||
version_id,
|
||||
file_id,
|
||||
)
|
||||
if result:
|
||||
return result
|
||||
except RateLimitError as exc:
|
||||
rate_limited = True
|
||||
logger.warning(
|
||||
"Provider %s is rate-limited (retry_after=%.0fs); not failing over to other network providers",
|
||||
label,
|
||||
exc.retry_after or 0,
|
||||
)
|
||||
continue
|
||||
except Exception as e:
|
||||
logger.debug(
|
||||
"Provider %s failed for get_version_file_mini: %s", label, e
|
||||
)
|
||||
continue
|
||||
return None
|
||||
|
||||
def _iter_providers(self):
|
||||
return zip(self.providers, self._provider_labels)
|
||||
|
||||
@@ -791,6 +838,16 @@ class RateLimitRetryingProvider(ModelMetadataProvider):
|
||||
async def get_creator_model_count(self, username: str) -> Optional[int]:
|
||||
return await self._provider.get_creator_model_count(username)
|
||||
|
||||
async def get_version_file_mini(
|
||||
self, version_id: int, file_id: int
|
||||
) -> Optional[Dict[str, Any]]:
|
||||
return await self._rate_limit_helper.run(
|
||||
self._label,
|
||||
self._provider.get_version_file_mini,
|
||||
version_id,
|
||||
file_id,
|
||||
)
|
||||
|
||||
class ModelMetadataProviderManager:
|
||||
"""Manager for selecting and using model metadata providers"""
|
||||
|
||||
|
||||
@@ -52,7 +52,6 @@ class PersistentRecipeCache:
|
||||
"file_mtime",
|
||||
"file_size",
|
||||
"favorite",
|
||||
"repair_version",
|
||||
"preview_nsfw_level",
|
||||
"loras_json",
|
||||
"checkpoint_json",
|
||||
@@ -442,7 +441,6 @@ class PersistentRecipeCache:
|
||||
file_mtime REAL,
|
||||
file_size INTEGER,
|
||||
favorite INTEGER DEFAULT 0,
|
||||
repair_version INTEGER DEFAULT 0,
|
||||
preview_nsfw_level INTEGER DEFAULT 0,
|
||||
loras_json TEXT,
|
||||
checkpoint_json TEXT,
|
||||
@@ -541,7 +539,6 @@ class PersistentRecipeCache:
|
||||
file_mtime,
|
||||
file_size,
|
||||
1 if recipe.get("favorite") else 0,
|
||||
int(recipe.get("repair_version") or 0),
|
||||
int(recipe.get("preview_nsfw_level") or 0),
|
||||
loras_json,
|
||||
checkpoint_json,
|
||||
@@ -599,7 +596,6 @@ class PersistentRecipeCache:
|
||||
"created_date": row["created_date"] or 0.0,
|
||||
"modified": row["modified"] or 0.0,
|
||||
"favorite": bool(row["favorite"]),
|
||||
"repair_version": row["repair_version"] or 0,
|
||||
"preview_nsfw_level": row["preview_nsfw_level"] or 0,
|
||||
"has_workflow": bool(row["has_workflow"]),
|
||||
"loras": loras,
|
||||
|
||||
@@ -94,8 +94,6 @@ class RecipeScanner:
|
||||
cls._instance._civitai_client = None # Will be lazily initialized
|
||||
return cls._instance
|
||||
|
||||
REPAIR_VERSION = 4
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
lora_scanner: Optional[LoraScanner] = None,
|
||||
@@ -811,207 +809,6 @@ class RecipeScanner:
|
||||
"""Check if cancellation has been requested."""
|
||||
return self._cancel_requested
|
||||
|
||||
async def repair_all_recipes(
|
||||
self, progress_callback: Optional[Callable[[Dict[str, Any]], Any]] = None
|
||||
) -> Dict[str, Any]:
|
||||
"""Repair all recipes by enrichment with Civitai and embedded metadata.
|
||||
|
||||
Args:
|
||||
persistence_service: Service for saving updated recipes
|
||||
progress_callback: Optional callback for progress updates
|
||||
|
||||
Returns:
|
||||
Dict summary of repair results
|
||||
"""
|
||||
if progress_callback:
|
||||
await progress_callback({"status": "started"})
|
||||
async with self._mutation_lock:
|
||||
cache = await self.get_cached_data()
|
||||
all_recipes = list(cache.raw_data)
|
||||
total = len(all_recipes)
|
||||
repaired_count = 0
|
||||
skipped_count = 0
|
||||
errors_count = 0
|
||||
|
||||
civitai_client = await self._get_civitai_client()
|
||||
self.reset_cancellation()
|
||||
|
||||
for i, recipe in enumerate(all_recipes):
|
||||
if self.is_cancelled():
|
||||
logger.info("Recipe repair cancelled by user")
|
||||
if progress_callback:
|
||||
await progress_callback(
|
||||
{
|
||||
"status": "cancelled",
|
||||
"current": i,
|
||||
"total": total,
|
||||
"repaired": repaired_count,
|
||||
"skipped": skipped_count,
|
||||
"errors": errors_count,
|
||||
}
|
||||
)
|
||||
return {
|
||||
"success": False,
|
||||
"status": "cancelled",
|
||||
"repaired": repaired_count,
|
||||
"skipped": skipped_count,
|
||||
"errors": errors_count,
|
||||
"total": total,
|
||||
}
|
||||
|
||||
try:
|
||||
# Report progress
|
||||
if progress_callback:
|
||||
await progress_callback(
|
||||
{
|
||||
"status": "processing",
|
||||
"current": i + 1,
|
||||
"total": total,
|
||||
"recipe_name": recipe.get("name", "Unknown"),
|
||||
}
|
||||
)
|
||||
|
||||
if await self._repair_single_recipe(recipe, civitai_client):
|
||||
repaired_count += 1
|
||||
else:
|
||||
skipped_count += 1
|
||||
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"Error repairing recipe {recipe.get('file_path')}: {e}"
|
||||
)
|
||||
errors_count += 1
|
||||
|
||||
# Final progress update
|
||||
if progress_callback:
|
||||
await progress_callback(
|
||||
{
|
||||
"status": "completed",
|
||||
"repaired": repaired_count,
|
||||
"skipped": skipped_count,
|
||||
"errors": errors_count,
|
||||
"total": total,
|
||||
}
|
||||
)
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"repaired": repaired_count,
|
||||
"skipped": skipped_count,
|
||||
"errors": errors_count,
|
||||
"total": total,
|
||||
}
|
||||
|
||||
async def repair_recipe_by_id(self, recipe_id: str) -> Dict[str, Any]:
|
||||
"""Repair a single recipe by its ID.
|
||||
|
||||
Args:
|
||||
recipe_id: ID of the recipe to repair
|
||||
|
||||
Returns:
|
||||
Dict summary of repair result
|
||||
"""
|
||||
async with self._mutation_lock:
|
||||
# Get raw recipe from cache directly to avoid formatted fields
|
||||
cache = await self.get_cached_data()
|
||||
recipe = next(
|
||||
(r for r in cache.raw_data if str(r.get("id", "")) == recipe_id), None
|
||||
)
|
||||
|
||||
if not recipe:
|
||||
raise RecipeNotFoundError(f"Recipe {recipe_id} not found")
|
||||
|
||||
civitai_client = await self._get_civitai_client()
|
||||
success = await self._repair_single_recipe(recipe, civitai_client)
|
||||
|
||||
# If successfully repaired, we should return the formatted version for the UI
|
||||
return {
|
||||
"success": True,
|
||||
"repaired": 1 if success else 0,
|
||||
"skipped": 0 if success else 1,
|
||||
"recipe": await self.get_recipe_by_id(recipe_id) if success else recipe,
|
||||
}
|
||||
|
||||
async def _repair_single_recipe(
|
||||
self, recipe: Dict[str, Any], civitai_client: Any
|
||||
) -> bool:
|
||||
"""Internal helper to repair a single recipe object.
|
||||
|
||||
Args:
|
||||
recipe: The recipe dictionary to repair (modified in-place)
|
||||
civitai_client: Authenticated Civitai client
|
||||
|
||||
Returns:
|
||||
bool: True if recipe was repaired or updated, False if skipped
|
||||
"""
|
||||
# 1. Skip if already at latest repair version
|
||||
if recipe.get("repair_version", 0) >= self.REPAIR_VERSION:
|
||||
return False
|
||||
|
||||
# 1.5 Detect and clear corrupted checkpoint (LoRA data saved as checkpoint).
|
||||
# A checkpoint whose modelVersionId also appears in a LoRA entry is
|
||||
# definitely wrong — the CivitAI import code used to pick
|
||||
# modelVersionIds[0] as the checkpoint, which was often a LoRA.
|
||||
# Clearing it lets the enrichment flow re-resolve the correct
|
||||
# checkpoint from CivitAI image metadata.
|
||||
cp = recipe.get("checkpoint")
|
||||
lora_mvids = {
|
||||
l.get("modelVersionId")
|
||||
for l in recipe.get("loras", [])
|
||||
if l.get("modelVersionId")
|
||||
}
|
||||
if cp and cp.get("modelVersionId") and cp["modelVersionId"] in lora_mvids:
|
||||
cp_mvid = cp["modelVersionId"]
|
||||
logger.info(
|
||||
"Recipe %s: checkpoint modelVersionId %s matches a LoRA — "
|
||||
"clearing corrupted checkpoint and removing matching LoRA entry",
|
||||
recipe.get("id"),
|
||||
cp_mvid,
|
||||
)
|
||||
recipe["checkpoint"] = None
|
||||
recipe["loras"] = [
|
||||
l for l in recipe.get("loras", [])
|
||||
if l.get("modelVersionId") != cp_mvid
|
||||
]
|
||||
|
||||
# 2. Identification: Is repair needed?
|
||||
has_checkpoint = (
|
||||
"checkpoint" in recipe
|
||||
and recipe["checkpoint"]
|
||||
and recipe["checkpoint"].get("name")
|
||||
)
|
||||
gen_params = recipe.get("gen_params", {})
|
||||
has_prompt = bool(gen_params.get("prompt"))
|
||||
|
||||
needs_repair = not has_checkpoint or not has_prompt
|
||||
|
||||
if not needs_repair:
|
||||
# Even if no repair needed, we mark it with version if it was processed
|
||||
# Always update and save because if we are here, the version is old (checked in step 1)
|
||||
recipe["repair_version"] = self.REPAIR_VERSION
|
||||
await self._save_recipe_persistently(recipe)
|
||||
return True
|
||||
|
||||
# 3. Use Enricher to repair/enrich
|
||||
try:
|
||||
from ..recipes.enrichment import RecipeEnricher
|
||||
|
||||
updated = await RecipeEnricher.enrich_recipe(recipe, civitai_client)
|
||||
except Exception as e:
|
||||
logger.error(f"Error enriching recipe {recipe.get('id')}: {e}")
|
||||
updated = False
|
||||
|
||||
# 4. Mark version and save if updated or just marking version
|
||||
# If we updated it, OR if the version is old (which we know it is if we are here), save it.
|
||||
# Actually, if we are here and updated is False, it means we tried to repair but couldn't/didn't need to.
|
||||
# But we still want to mark it as processed so we don't try again until version bump.
|
||||
if updated or recipe.get("repair_version", 0) < self.REPAIR_VERSION:
|
||||
recipe["repair_version"] = self.REPAIR_VERSION
|
||||
await self._save_recipe_persistently(recipe)
|
||||
return True
|
||||
|
||||
return False
|
||||
|
||||
async def rematch_recipe_by_id(self, recipe_id: str) -> Dict[str, Any]:
|
||||
"""Rematch a single recipe's deleted lora/checkpoint entries locally.
|
||||
|
||||
|
||||
@@ -20,8 +20,6 @@ class WebSocketManager:
|
||||
self._last_init_progress: Dict[str, Dict[str, Any]] = {}
|
||||
# Add auto-organize progress tracking
|
||||
self._auto_organize_progress: Optional[Dict[str, Any]] = None
|
||||
# Add recipe repair progress tracking
|
||||
self._recipe_repair_progress: Optional[Dict[str, Any]] = None
|
||||
# Add recipe rematch progress tracking
|
||||
self._recipe_rematch_progress: Optional[Dict[str, Any]] = None
|
||||
self._auto_organize_lock = asyncio.Lock()
|
||||
@@ -193,14 +191,6 @@ class WebSocketManager:
|
||||
# Broadcast via WebSocket
|
||||
await self.broadcast(data)
|
||||
|
||||
async def broadcast_recipe_repair_progress(self, data: Dict[str, Any]):
|
||||
"""Broadcast recipe repair progress to connected clients"""
|
||||
# Store progress data in memory
|
||||
self._recipe_repair_progress = data
|
||||
|
||||
# Broadcast via WebSocket
|
||||
await self.broadcast(data)
|
||||
|
||||
def get_auto_organize_progress(self) -> Optional[Dict[str, Any]]:
|
||||
"""Get current auto-organize progress"""
|
||||
return self._auto_organize_progress
|
||||
@@ -209,22 +199,6 @@ class WebSocketManager:
|
||||
"""Clear auto-organize progress data"""
|
||||
self._auto_organize_progress = None
|
||||
|
||||
def get_recipe_repair_progress(self) -> Optional[Dict[str, Any]]:
|
||||
"""Get current recipe repair progress"""
|
||||
return self._recipe_repair_progress
|
||||
|
||||
def cleanup_recipe_repair_progress(self):
|
||||
"""Clear recipe repair progress data if it is in a finished state"""
|
||||
if self._recipe_repair_progress and self._recipe_repair_progress.get('status') in ['completed', 'cancelled', 'error']:
|
||||
self._recipe_repair_progress = None
|
||||
|
||||
def is_recipe_repair_running(self) -> bool:
|
||||
"""Check if recipe repair is currently running"""
|
||||
if not self._recipe_repair_progress:
|
||||
return False
|
||||
status = self._recipe_repair_progress.get('status')
|
||||
return status in ['started', 'processing']
|
||||
|
||||
async def broadcast_recipe_rematch_progress(self, data: Dict[str, Any]):
|
||||
"""Broadcast recipe rematch progress to connected clients"""
|
||||
# Store progress data in memory
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
[project]
|
||||
name = "comfyui-lora-manager"
|
||||
description = "Revolutionize your workflow with the ultimate LoRA companion for ComfyUI!"
|
||||
version = "1.2.1"
|
||||
version = "1.2.2"
|
||||
license = {file = "LICENSE"}
|
||||
dependencies = [
|
||||
"aiohttp",
|
||||
|
||||
@@ -174,7 +174,7 @@
|
||||
z-index: var(--z-toast);
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
align-items: flex-end;
|
||||
/* No align-items (defaults to stretch) so every toast shares one equal width */
|
||||
gap: 10px;
|
||||
padding: 8px 20px 0; /* Small breathing room below the header */
|
||||
pointer-events: none; /* Allow clicking through the container */
|
||||
|
||||
@@ -20,7 +20,6 @@ const RECIPE_ENDPOINTS = {
|
||||
move: '/api/lm/recipe/move',
|
||||
moveBulk: '/api/lm/recipes/move-bulk',
|
||||
bulkDelete: '/api/lm/recipes/bulk-delete',
|
||||
repairBulk: '/api/lm/recipes/repair-bulk',
|
||||
rematchBulk: '/api/lm/recipes/rematch-bulk',
|
||||
rematchSingle: '/api/lm/recipe/{recipe_id}/rematch',
|
||||
};
|
||||
@@ -678,38 +677,6 @@ export class RecipeSidebarApiClient {
|
||||
};
|
||||
}
|
||||
|
||||
async repairBulkModels(filePaths) {
|
||||
if (!filePaths || filePaths.length === 0) {
|
||||
throw new Error('No file paths provided');
|
||||
}
|
||||
|
||||
const recipeIds = filePaths
|
||||
.map((path) => extractRecipeId(path))
|
||||
.filter((id) => !!id);
|
||||
|
||||
if (recipeIds.length === 0) {
|
||||
throw new Error('No recipe IDs could be derived from file paths');
|
||||
}
|
||||
|
||||
const response = await fetch(this.apiConfig.endpoints.repairBulk, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({
|
||||
recipe_ids: recipeIds,
|
||||
}),
|
||||
});
|
||||
|
||||
const result = await response.json();
|
||||
|
||||
if (!response.ok || !result.success) {
|
||||
throw new Error(result.error || 'Failed to repair recipes');
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
async rematchBulkModels(filePaths) {
|
||||
if (!filePaths || filePaths.length === 0) {
|
||||
throw new Error('No file paths provided');
|
||||
|
||||
@@ -41,13 +41,9 @@ export class BulkContextMenu extends BaseContextMenu {
|
||||
const autoOrganizeItem = this.menu.querySelector('[data-action="auto-organize"]');
|
||||
const deleteAllItem = this.menu.querySelector('[data-action="delete-all"]');
|
||||
const downloadMissingLorasItem = this.menu.querySelector('[data-action="download-missing-loras"]');
|
||||
const repairMetadataItem = this.menu.querySelector('[data-action="repair-metadata"]');
|
||||
const reimportMetadataItem = this.menu.querySelector('[data-action="reimport-metadata"]');
|
||||
const rematchMetadataItem = this.menu.querySelector('[data-action="rematch-metadata"]');
|
||||
|
||||
if (repairMetadataItem) {
|
||||
repairMetadataItem.style.display = config.repairMetadata ? 'flex' : 'none';
|
||||
}
|
||||
if (reimportMetadataItem) {
|
||||
reimportMetadataItem.style.display = config.reimportMetadata ? 'flex' : 'none';
|
||||
}
|
||||
@@ -283,9 +279,6 @@ export class BulkContextMenu extends BaseContextMenu {
|
||||
case 'delete-all':
|
||||
bulkManager.showBulkDeleteModal();
|
||||
break;
|
||||
case 'repair-metadata':
|
||||
bulkManager.repairSelectedRecipes();
|
||||
break;
|
||||
case 'rematch-metadata':
|
||||
bulkManager.rematchSelectedRecipes();
|
||||
break;
|
||||
|
||||
@@ -23,7 +23,6 @@ export class GlobalContextMenu extends BaseContextMenu {
|
||||
const downloadExamplesItem = this.menu.querySelector('[data-action="download-example-images"]');
|
||||
const cleanupExamplesItem = this.menu.querySelector('[data-action="cleanup-example-images-folders"]');
|
||||
const excludedModelsItem = this.menu.querySelector('[data-action="manage-excluded-models"]');
|
||||
const repairRecipesItem = this.menu.querySelector('[data-action="repair-recipes"]');
|
||||
const rematchRecipesItem = this.menu.querySelector('[data-action="rematch-recipes"]');
|
||||
const groupByModelItem = this.menu.querySelector('[data-action="toggle-group-by-model"]');
|
||||
const groupByModelCheck = groupByModelItem?.querySelector('.check-indicator');
|
||||
@@ -41,7 +40,6 @@ export class GlobalContextMenu extends BaseContextMenu {
|
||||
cleanupExamplesItem?.classList.add('hidden');
|
||||
excludedModelsItem?.classList.add('hidden');
|
||||
groupByModelItem?.classList.add('hidden');
|
||||
repairRecipesItem?.classList.remove('hidden');
|
||||
rematchRecipesItem?.classList.remove('hidden');
|
||||
} else {
|
||||
modelUpdateItem?.classList.remove('hidden');
|
||||
@@ -50,7 +48,6 @@ export class GlobalContextMenu extends BaseContextMenu {
|
||||
cleanupExamplesItem?.classList.remove('hidden');
|
||||
excludedModelsItem?.classList.remove('hidden');
|
||||
groupByModelItem?.classList.remove('hidden');
|
||||
repairRecipesItem?.classList.add('hidden');
|
||||
rematchRecipesItem?.classList.add('hidden');
|
||||
}
|
||||
|
||||
@@ -95,11 +92,6 @@ export class GlobalContextMenu extends BaseContextMenu {
|
||||
console.error('Failed to refresh missing license metadata:', error);
|
||||
});
|
||||
break;
|
||||
case 'repair-recipes':
|
||||
this.repairRecipes(menuItem).catch((error) => {
|
||||
console.error('Failed to repair recipes:', error);
|
||||
});
|
||||
break;
|
||||
case 'rematch-recipes':
|
||||
this.rematchRecipes(menuItem).catch((error) => {
|
||||
console.error('Failed to rematch recipes:', error);
|
||||
@@ -371,99 +363,6 @@ export class GlobalContextMenu extends BaseContextMenu {
|
||||
return `${displayName}s`;
|
||||
}
|
||||
|
||||
async repairRecipes(menuItem) {
|
||||
if (this._repairInProgress) {
|
||||
return;
|
||||
}
|
||||
|
||||
this._repairInProgress = true;
|
||||
menuItem?.classList.add('disabled');
|
||||
|
||||
const loadingMessage = translate(
|
||||
'globalContextMenu.repairRecipes.loading',
|
||||
{},
|
||||
'Repairing recipe data...'
|
||||
);
|
||||
|
||||
const progressUI = state.loadingManager?.showEnhancedProgress(loadingMessage);
|
||||
progressUI?.showCancelButton(() => this.cancelRepair());
|
||||
|
||||
try {
|
||||
const response = await fetch('/api/lm/recipes/repair', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
});
|
||||
|
||||
const result = await response.json();
|
||||
if (!response.ok || !result.success) {
|
||||
throw new Error(result.error || 'Failed to start repair');
|
||||
}
|
||||
|
||||
// Poll for progress (or wait for WebSocket if preferred, but polling is simpler for this implementation)
|
||||
let isComplete = false;
|
||||
while (!isComplete && this._repairInProgress) {
|
||||
const progressResponse = await fetch('/api/lm/recipes/repair-progress');
|
||||
if (progressResponse.ok) {
|
||||
const progressResult = await progressResponse.json();
|
||||
if (progressResult.success && progressResult.progress) {
|
||||
const p = progressResult.progress;
|
||||
if (p.status === 'processing') {
|
||||
const percent = (p.current / p.total) * 100;
|
||||
progressUI?.updateProgress(percent, p.recipe_name, `${loadingMessage} (${p.current}/${p.total})`);
|
||||
} else if (p.status === 'completed') {
|
||||
isComplete = true;
|
||||
progressUI?.complete(translate(
|
||||
'globalContextMenu.repairRecipes.success',
|
||||
{ count: p.repaired },
|
||||
`Repaired ${p.repaired} recipes.`
|
||||
));
|
||||
showToast('globalContextMenu.repairRecipes.success', { count: p.repaired }, 'success');
|
||||
// Refresh recipes page if active
|
||||
if (window.recipesPage) {
|
||||
window.recipesPage.refresh();
|
||||
}
|
||||
} else if (p.status === 'error') {
|
||||
throw new Error(p.error || 'Repair failed');
|
||||
} else if (p.status === 'cancelled') {
|
||||
isComplete = true;
|
||||
progressUI?.complete(translate(
|
||||
'globalContextMenu.repairRecipes.cancelled',
|
||||
{ count: p.repaired },
|
||||
`Repair cancelled. ${p.repaired} recipes were repaired.`
|
||||
));
|
||||
showToast('globalContextMenu.repairRecipes.cancelled', { count: p.repaired }, 'info');
|
||||
}
|
||||
} else if (progressResponse.status === 404) {
|
||||
// Progress might have finished quickly and been cleaned up
|
||||
isComplete = true;
|
||||
progressUI?.complete();
|
||||
}
|
||||
}
|
||||
|
||||
if (!isComplete) {
|
||||
await new Promise(resolve => setTimeout(resolve, 1000));
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Recipe repair failed:', error);
|
||||
progressUI?.complete(translate('globalContextMenu.repairRecipes.error', { message: error.message }, 'Repair failed: {message}'));
|
||||
showToast('globalContextMenu.repairRecipes.error', { message: error.message }, 'error');
|
||||
} finally {
|
||||
this._repairInProgress = false;
|
||||
menuItem?.classList.remove('disabled');
|
||||
}
|
||||
}
|
||||
|
||||
async cancelRepair() {
|
||||
try {
|
||||
await fetch('/api/lm/recipes/cancel-repair', {
|
||||
method: 'POST',
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('Failed to cancel recipe repair:', error);
|
||||
}
|
||||
}
|
||||
|
||||
async rematchRecipes(menuItem) {
|
||||
if (this._rematchInProgress) {
|
||||
return;
|
||||
|
||||
@@ -6,6 +6,7 @@ import { setSessionItem, removeSessionItem } from '../../utils/storageHelpers.js
|
||||
import { updateRecipeMetadata } from '../../api/recipeApi.js';
|
||||
import { state } from '../../state/index.js';
|
||||
import { moveManager } from '../../managers/MoveManager.js';
|
||||
import { probeExtension, delegateReimport, getCivitaiImageInfo } from '../../utils/extensionReimportBridge.js';
|
||||
|
||||
export class RecipeContextMenu extends BaseContextMenu {
|
||||
constructor() {
|
||||
@@ -93,10 +94,6 @@ export class RecipeContextMenu extends BaseContextMenu {
|
||||
// Download missing LoRAs
|
||||
this.downloadMissingLoRAs(recipeId);
|
||||
break;
|
||||
case 'repair':
|
||||
// Repair recipe metadata
|
||||
this.repairRecipe(recipeId);
|
||||
break;
|
||||
case 'rematch':
|
||||
// Rematch recipe resources to local models
|
||||
this.rematchRecipe(recipeId);
|
||||
@@ -297,44 +294,6 @@ export class RecipeContextMenu extends BaseContextMenu {
|
||||
}
|
||||
}
|
||||
|
||||
// Repair recipe metadata
|
||||
async repairRecipe(recipeId) {
|
||||
if (!recipeId) {
|
||||
showToast('recipes.contextMenu.repair.missingId', {}, 'error');
|
||||
return;
|
||||
}
|
||||
|
||||
try {
|
||||
showToast('recipes.contextMenu.repair.starting', {}, 'info');
|
||||
|
||||
const response = await fetch(`/api/lm/recipe/${recipeId}/repair`, {
|
||||
method: 'POST'
|
||||
});
|
||||
const result = await response.json();
|
||||
|
||||
if (result.success) {
|
||||
if (result.repaired > 0) {
|
||||
showToast('recipes.contextMenu.repair.success', {}, 'success');
|
||||
const detailResponse = await fetch(`/api/lm/recipe/${recipeId}`);
|
||||
if (detailResponse.ok) {
|
||||
const updatedRecipe = await detailResponse.json();
|
||||
const filePath = this.currentCard?.dataset?.filepath;
|
||||
if (filePath && state.virtualScroller) {
|
||||
state.virtualScroller.updateSingleItem(filePath, updatedRecipe);
|
||||
}
|
||||
}
|
||||
} else {
|
||||
showToast('recipes.contextMenu.repair.skipped', {}, 'info');
|
||||
}
|
||||
} else {
|
||||
throw new Error(result.error || 'Repair failed');
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Error repairing recipe:', error);
|
||||
showToast('recipes.contextMenu.repair.failed', { message: error.message }, 'error');
|
||||
}
|
||||
}
|
||||
|
||||
async rematchRecipe(recipeId) {
|
||||
if (!recipeId) {
|
||||
showToast('toast.recipes.rematchFailed', { message: 'Missing recipe ID' }, 'error');
|
||||
@@ -397,6 +356,24 @@ export class RecipeContextMenu extends BaseContextMenu {
|
||||
return;
|
||||
}
|
||||
|
||||
// Recipes imported from a CivitAI image page can carry incomplete
|
||||
// metadata (0 LoRAs); the companion browser extension can re-import
|
||||
// them with the full page data. Fall back to the native path whenever
|
||||
// the extension is absent, unlicensed, or the delegation fails.
|
||||
const recipeItem = state.virtualScroller?.items?.find(item => item?.id === recipeId);
|
||||
const civitaiImage = getCivitaiImageInfo(recipeItem?.source_path);
|
||||
if (civitaiImage) {
|
||||
try {
|
||||
const probe = await probeExtension();
|
||||
if (probe?.supported && probe?.licenseValid) {
|
||||
await this.reimportViaExtension(recipeId, civitaiImage, recipeItem?.title || '');
|
||||
return;
|
||||
}
|
||||
} catch (error) {
|
||||
console.warn('Extension re-import unavailable, using native path:', error);
|
||||
}
|
||||
}
|
||||
|
||||
state.loadingManager.showSimpleLoading('Re-importing recipe from source...');
|
||||
|
||||
try {
|
||||
@@ -419,6 +396,34 @@ export class RecipeContextMenu extends BaseContextMenu {
|
||||
showToast('recipes.contextMenu.reimport.failed', { message: error.message }, 'error');
|
||||
}
|
||||
}
|
||||
|
||||
// Re-import a single CivitAI-image recipe through the companion browser
|
||||
// extension. Throws on delegation failure so the caller can fall back to
|
||||
// the native path.
|
||||
async reimportViaExtension(recipeId, civitaiImage, title) {
|
||||
state.loadingManager.showSimpleLoading('Re-importing recipe via browser extension...');
|
||||
|
||||
try {
|
||||
const { failed } = await delegateReimport([{
|
||||
recipeId,
|
||||
imageId: civitaiImage.imageId,
|
||||
imageUrl: civitaiImage.imageUrl,
|
||||
title,
|
||||
}]);
|
||||
|
||||
state.loadingManager.hide();
|
||||
if (failed > 0) {
|
||||
showToast('recipes.contextMenu.reimport.failed', { message: 'Extension re-import failed' }, 'error');
|
||||
} else {
|
||||
showToast('toast.recipes.reimportSuccess', {}, 'success');
|
||||
}
|
||||
const { resetAndReload } = await import('../../api/recipeApi.js');
|
||||
resetAndReload(false, { preserveScroll: false });
|
||||
} catch (error) {
|
||||
state.loadingManager.hide();
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Mix in shared methods from ModelContextMenuMixin
|
||||
|
||||
@@ -2877,12 +2877,14 @@ class RecipeModal {
|
||||
|
||||
canDownloadLora(lora) {
|
||||
if (!lora) return false;
|
||||
const modelId = lora.modelId || lora.modelID || lora.model_id;
|
||||
const versionId = lora.id || lora.modelVersionId;
|
||||
// Direct download needs both identifiers; a hash alone is enough
|
||||
// because downloadRecipeLora resolves it to a version on demand —
|
||||
// the same fallback the bulk "download missing" flow uses.
|
||||
return !!((modelId && versionId) || lora.hash);
|
||||
// A bare CivitAI version id is enough: it uniquely pins the exact
|
||||
// file, and downloadRecipeLora resolves the owning model id from the
|
||||
// version on demand (the same fallback the bulk "download missing"
|
||||
// flow uses). A hash alone is likewise sufficient. A model id without
|
||||
// an exact version id is NOT enough — downloading the model's latest
|
||||
// version could silently mismatch the recipe's pinned version.
|
||||
return !!(versionId || lora.hash);
|
||||
}
|
||||
|
||||
renderCivitaiLink(url) {
|
||||
@@ -2991,6 +2993,9 @@ class RecipeModal {
|
||||
* Resolve the Civitai model/version identifiers needed for download.
|
||||
* Recipe LoRAs parsed from PNG metadata often carry only a hash; resolve
|
||||
* it through the same endpoint the bulk "download missing" flow uses.
|
||||
* Version-only entries (page-imported recipes whose CivitAI version has
|
||||
* no sha256) are resolved through the version endpoint, which returns
|
||||
* the owning model id.
|
||||
*/
|
||||
async resolveLoraDownloadIdentifiers(lora) {
|
||||
let modelId = lora.modelId || lora.modelID || lora.model_id;
|
||||
@@ -3001,21 +3006,41 @@ class RecipeModal {
|
||||
return { modelId, versionId, versionName };
|
||||
}
|
||||
|
||||
if (!lora.hash) {
|
||||
return null;
|
||||
// Hash-only entries (PNG/recipe-JSON imports): resolve the owning
|
||||
// model/version through the same endpoint the bulk "download
|
||||
// missing" flow uses.
|
||||
if (lora.hash) {
|
||||
const response = await fetch(`/api/lm/loras/civitai/model/hash/${lora.hash}`);
|
||||
const versionInfo = await response.json();
|
||||
if (versionInfo?.error) {
|
||||
return null;
|
||||
}
|
||||
|
||||
modelId = versionInfo.modelId || versionInfo.model?.id;
|
||||
versionId = versionInfo.id;
|
||||
versionName = versionInfo.name || versionName;
|
||||
|
||||
return modelId && versionId ? { modelId, versionId, versionName } : null;
|
||||
}
|
||||
|
||||
const response = await fetch(`/api/lm/loras/civitai/model/hash/${lora.hash}`);
|
||||
const versionInfo = await response.json();
|
||||
if (versionInfo?.error) {
|
||||
return null;
|
||||
// Version-only entries (page-imported recipes whose CivitAI versions
|
||||
// expose no sha256): the version id still pins the exact file, so
|
||||
// resolve the owning model id from the version endpoint on demand.
|
||||
if (versionId) {
|
||||
const response = await fetch(`/api/lm/loras/civitai/model/version/${versionId}`);
|
||||
const versionInfo = await response.json();
|
||||
if (!versionInfo || versionInfo?.error === 'Model not found') {
|
||||
return null;
|
||||
}
|
||||
|
||||
modelId = versionInfo.modelId || versionInfo.model?.id;
|
||||
versionId = versionInfo.id || versionId;
|
||||
versionName = versionInfo.name || versionName;
|
||||
|
||||
return modelId && versionId ? { modelId, versionId, versionName } : null;
|
||||
}
|
||||
|
||||
modelId = versionInfo.modelId || versionInfo.model?.id;
|
||||
versionId = versionInfo.id;
|
||||
versionName = versionInfo.name || versionName;
|
||||
|
||||
return modelId && versionId ? { modelId, versionId, versionName } : null;
|
||||
return null;
|
||||
}
|
||||
|
||||
/**
|
||||
|
||||
@@ -10,6 +10,7 @@ import { createBaseModelPicker, inferBaseModelsFromFilepaths } from '../componen
|
||||
import { getPriorityTagSuggestions } from '../utils/priorityTagHelpers.js';
|
||||
import { eventManager } from '../utils/EventManager.js';
|
||||
import { translate } from '../utils/i18nHelpers.js';
|
||||
import { probeExtension, delegateReimport, getCivitaiImageInfo } from '../utils/extensionReimportBridge.js';
|
||||
import { getNsfwLevelSelector } from '../components/shared/NsfwLevelSelector.js';
|
||||
|
||||
export class BulkManager {
|
||||
@@ -103,7 +104,6 @@ export class BulkManager {
|
||||
skipMetadataRefresh: false,
|
||||
setFavorite: true,
|
||||
unfavorite: true,
|
||||
repairMetadata: true,
|
||||
reimportMetadata: true,
|
||||
rematchMetadata: true
|
||||
}
|
||||
@@ -858,17 +858,74 @@ export class BulkManager {
|
||||
`Re-importing recipe 1/${total}...`
|
||||
);
|
||||
|
||||
// Partition the selection: recipes sourced from a CivitAI image page
|
||||
// can be delegated to the companion browser extension (which scrapes
|
||||
// the full page metadata); everything else uses the native endpoint.
|
||||
const delegatable = [];
|
||||
const nativeFilePaths = [];
|
||||
for (const filePath of filePaths) {
|
||||
const recipeItem = recipeMap.get(filePath);
|
||||
const civitaiImage = getCivitaiImageInfo(recipeItem?.source_path);
|
||||
if (civitaiImage && recipeItem?.id) {
|
||||
delegatable.push({
|
||||
filePath,
|
||||
recipeId: recipeItem.id,
|
||||
imageId: civitaiImage.imageId,
|
||||
imageUrl: civitaiImage.imageUrl,
|
||||
title: recipeItem.title || '',
|
||||
});
|
||||
} else {
|
||||
nativeFilePaths.push(filePath);
|
||||
}
|
||||
}
|
||||
|
||||
// Probe once; on any probe/delegate failure the delegatable recipes
|
||||
// fall back to the native sequential loop below.
|
||||
if (delegatable.length > 0) {
|
||||
try {
|
||||
const probe = await probeExtension();
|
||||
if (probe?.supported && probe?.licenseValid) {
|
||||
const batchResult = await delegateReimport(
|
||||
delegatable.map(({ recipeId, imageId, imageUrl, title }) => ({
|
||||
recipeId, imageId, imageUrl, title,
|
||||
})),
|
||||
{
|
||||
onProgress: (progress) => {
|
||||
progressUI.updateProgress(
|
||||
Math.floor(((progress.current || 0) / total) * 100),
|
||||
progress.title || '',
|
||||
translate('toast.recipes.reimportingViaExtension', {
|
||||
current: progress.current || 0,
|
||||
total,
|
||||
})
|
||||
);
|
||||
},
|
||||
}
|
||||
);
|
||||
completed += batchResult.completed;
|
||||
failed += batchResult.failed;
|
||||
} else {
|
||||
nativeFilePaths.push(...delegatable.map(entry => entry.filePath));
|
||||
}
|
||||
} catch (error) {
|
||||
console.warn('[reimportSelectedRecipes] extension delegation failed, using native path:', error);
|
||||
nativeFilePaths.push(...delegatable.map(entry => entry.filePath));
|
||||
}
|
||||
}
|
||||
|
||||
try {
|
||||
for (let i = 0; i < filePaths.length; i++) {
|
||||
const filePath = filePaths[i];
|
||||
const processedBeforeNative = completed + failed;
|
||||
for (let i = 0; i < nativeFilePaths.length; i++) {
|
||||
const filePath = nativeFilePaths[i];
|
||||
const recipeItem = recipeMap.get(filePath);
|
||||
const recipeId = recipeItem?.id;
|
||||
const recipeName = recipeItem?.title || recipeId || 'Unknown';
|
||||
const processed = processedBeforeNative + i;
|
||||
|
||||
progressUI.updateProgress(
|
||||
Math.floor((i / total) * 100),
|
||||
Math.floor((processed / total) * 100),
|
||||
recipeName,
|
||||
`Re-importing recipe ${Math.min(i + 1, total)}/${total}...`
|
||||
`Re-importing recipe ${Math.min(processed + 1, total)}/${total}...`
|
||||
);
|
||||
|
||||
if (!recipeId) {
|
||||
@@ -910,76 +967,6 @@ export class BulkManager {
|
||||
}
|
||||
}
|
||||
|
||||
async repairSelectedRecipes() {
|
||||
if (state.selectedModels.size === 0) {
|
||||
showToast('toast.recipes.noRecipesSelected', {}, 'warning');
|
||||
return;
|
||||
}
|
||||
|
||||
if (state.currentPageType !== 'recipes') {
|
||||
showToast('This operation is only available for recipes', {}, 'warning');
|
||||
return;
|
||||
}
|
||||
|
||||
try {
|
||||
const apiClient = this.getActiveApiClient();
|
||||
const filePaths = Array.from(state.selectedModels);
|
||||
|
||||
if (typeof apiClient.repairBulkModels !== 'function') {
|
||||
showToast('Bulk repair is not supported for this model type', {}, 'error');
|
||||
return;
|
||||
}
|
||||
|
||||
state.loadingManager.showSimpleLoading('Repairing recipe metadata...');
|
||||
|
||||
const result = await apiClient.repairBulkModels(filePaths);
|
||||
|
||||
if (result.success) {
|
||||
const total = result.total || filePaths.length;
|
||||
const repaired = result.repaired || 0;
|
||||
const skipped = result.skipped || 0;
|
||||
|
||||
const recipes = result.recipes || [];
|
||||
for (const recipe of recipes) {
|
||||
if (recipe.file_path) {
|
||||
state.virtualScroller.updateSingleItem(
|
||||
recipe.file_path,
|
||||
recipe
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
if (repaired > 0) {
|
||||
showToast(
|
||||
'toast.recipes.repairBulkComplete',
|
||||
{ repaired, skipped, total },
|
||||
'success'
|
||||
);
|
||||
} else {
|
||||
showToast(
|
||||
'toast.recipes.repairBulkSkipped',
|
||||
{ total },
|
||||
'info'
|
||||
);
|
||||
}
|
||||
|
||||
if (state.bulkMode) this.toggleBulkMode();
|
||||
} else {
|
||||
throw new Error(result.error || 'Bulk repair failed');
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Error during bulk recipe repair:', error);
|
||||
showToast('toast.recipes.repairBulkFailed', { message: error.message }, 'error');
|
||||
} finally {
|
||||
if (state.loadingManager?.hide) {
|
||||
state.loadingManager.hide();
|
||||
}
|
||||
if (typeof state.loadingManager?.restoreProgressBar === 'function') {
|
||||
state.loadingManager.restoreProgressBar();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
async rematchSelectedRecipes() {
|
||||
if (state.selectedModels.size === 0) {
|
||||
showToast('toast.recipes.noRecipesSelected', {}, 'warning');
|
||||
|
||||
@@ -0,0 +1,220 @@
|
||||
/**
|
||||
* Bridge to the companion LoRA Manager browser extension.
|
||||
*
|
||||
* The extension can re-import recipes sourced from CivitAI image pages with
|
||||
* the complete page metadata (internal trpc data scraped with the user's
|
||||
* session), fixing recipes that the native import (REST API + EXIF only)
|
||||
* saved with 0 LoRAs.
|
||||
*
|
||||
* Protocol: DOM CustomEvents on `document`; `detail` is ALWAYS a JSON
|
||||
* string on both sides.
|
||||
*
|
||||
* LM page -> extension: `lm:reimportProbe`, detail `{}`.
|
||||
* extension -> LM page: `lm:reimportProbeResult`,
|
||||
* detail `{supported, licenseValid, extensionVersion?, reason?}`.
|
||||
* LM page -> extension: `lm:reimportViaExtension`,
|
||||
* detail `{requestId, recipes: [{recipeId, imageId, imageUrl, title}]}`.
|
||||
* extension -> LM page: `lm:reimportProgress`,
|
||||
* detail `{requestId, current, total, recipeId, title, status, message?}`.
|
||||
* extension -> LM page: `lm:reimportBatchDone`,
|
||||
* detail `{requestId, completed, failed}`.
|
||||
*/
|
||||
|
||||
const PROBE_EVENT = 'lm:reimportProbe';
|
||||
const PROBE_RESULT_EVENT = 'lm:reimportProbeResult';
|
||||
const REIMPORT_EVENT = 'lm:reimportViaExtension';
|
||||
const PROGRESS_EVENT = 'lm:reimportProgress';
|
||||
const BATCH_DONE_EVENT = 'lm:reimportBatchDone';
|
||||
|
||||
const DEFAULT_PROBE_TIMEOUT_MS = 500;
|
||||
// Generous batch timeout; any progress event resets it (heartbeat).
|
||||
const DEFAULT_REIMPORT_TIMEOUT_MS = 3 * 60 * 1000;
|
||||
|
||||
// Mirrors py/utils/civitai_utils.py (_SUPPORTED_CIVITAI_PAGE_HOSTS).
|
||||
const SUPPORTED_CIVITAI_PAGE_HOSTS = new Set([
|
||||
'civitai.com',
|
||||
'civitai.red',
|
||||
'civitai.green',
|
||||
]);
|
||||
|
||||
/**
|
||||
* Parse the JSON-string `detail` of a protocol event.
|
||||
* @param {CustomEvent} event
|
||||
* @returns {object|null} Parsed detail object, or null when absent/invalid.
|
||||
*/
|
||||
function parseDetail(event) {
|
||||
try {
|
||||
const detail = JSON.parse(event?.detail ?? 'null');
|
||||
return detail && typeof detail === 'object' ? detail : null;
|
||||
} catch {
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Dispatch a protocol event with a JSON-stringified detail.
|
||||
* @param {string} type - Event name.
|
||||
* @param {object} payload - Detail payload (JSON-stringified).
|
||||
*/
|
||||
function dispatchProtocolEvent(type, payload) {
|
||||
document.dispatchEvent(
|
||||
new CustomEvent(type, { detail: JSON.stringify(payload ?? {}) })
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* Generate a correlation id for a re-import batch.
|
||||
* @returns {string}
|
||||
*/
|
||||
function generateRequestId() {
|
||||
if (globalThis.crypto?.randomUUID) {
|
||||
return globalThis.crypto.randomUUID();
|
||||
}
|
||||
return `lm-${Date.now()}-${Math.random().toString(36).slice(2, 10)}`;
|
||||
}
|
||||
|
||||
/**
|
||||
* Probe whether the companion extension is installed and usable.
|
||||
*
|
||||
* @param {{timeoutMs?: number}} [options]
|
||||
* @returns {Promise<{supported: boolean, licenseValid: boolean, extensionVersion?: string, reason?: string}|null>}
|
||||
* Resolves with the probe result, or null when the extension is absent or
|
||||
* too old to answer (timeout).
|
||||
*/
|
||||
export function probeExtension({ timeoutMs = DEFAULT_PROBE_TIMEOUT_MS } = {}) {
|
||||
return new Promise((resolve) => {
|
||||
let settled = false;
|
||||
const timer = setTimeout(() => finish(null), timeoutMs);
|
||||
|
||||
const finish = (value) => {
|
||||
if (settled) return;
|
||||
settled = true;
|
||||
clearTimeout(timer);
|
||||
document.removeEventListener(PROBE_RESULT_EVENT, onResult);
|
||||
resolve(value);
|
||||
};
|
||||
|
||||
const onResult = (event) => {
|
||||
const detail = parseDetail(event);
|
||||
if (!detail) return;
|
||||
finish({
|
||||
supported: Boolean(detail.supported),
|
||||
licenseValid: Boolean(detail.licenseValid),
|
||||
extensionVersion: detail.extensionVersion,
|
||||
reason: detail.reason,
|
||||
});
|
||||
};
|
||||
|
||||
document.addEventListener(PROBE_RESULT_EVENT, onResult);
|
||||
dispatchProtocolEvent(PROBE_EVENT, {});
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Delegate a batch of recipe re-imports to the companion extension.
|
||||
*
|
||||
* @param {Array<{recipeId: string, imageId: number, imageUrl: string, title: string}>} recipes
|
||||
* @param {{onProgress?: (progress: object) => void, timeoutMs?: number}} [options]
|
||||
* @returns {Promise<{completed: number, failed: number}>} Resolves on
|
||||
* `lm:reimportBatchDone`; rejects on timeout. Listeners are cleaned up in
|
||||
* all outcomes.
|
||||
*/
|
||||
export function delegateReimport(recipes, { onProgress, timeoutMs = DEFAULT_REIMPORT_TIMEOUT_MS } = {}) {
|
||||
return new Promise((resolve, reject) => {
|
||||
if (!Array.isArray(recipes) || recipes.length === 0) {
|
||||
reject(new Error('delegateReimport requires a non-empty recipe list'));
|
||||
return;
|
||||
}
|
||||
|
||||
const requestId = generateRequestId();
|
||||
let settled = false;
|
||||
let timer = null;
|
||||
|
||||
const cleanup = () => {
|
||||
clearTimeout(timer);
|
||||
document.removeEventListener(PROGRESS_EVENT, onProgressEvent);
|
||||
document.removeEventListener(BATCH_DONE_EVENT, onBatchDone);
|
||||
};
|
||||
const succeed = (value) => {
|
||||
if (settled) return;
|
||||
settled = true;
|
||||
cleanup();
|
||||
resolve(value);
|
||||
};
|
||||
const fail = (error) => {
|
||||
if (settled) return;
|
||||
settled = true;
|
||||
cleanup();
|
||||
reject(error);
|
||||
};
|
||||
const armTimer = () => {
|
||||
clearTimeout(timer);
|
||||
timer = setTimeout(
|
||||
() => fail(new Error('Extension re-import timed out')),
|
||||
timeoutMs
|
||||
);
|
||||
};
|
||||
|
||||
const onProgressEvent = (event) => {
|
||||
const detail = parseDetail(event);
|
||||
if (!detail || detail.requestId !== requestId) return;
|
||||
// Heartbeat: any progress for this batch resets the timeout.
|
||||
armTimer();
|
||||
if (typeof onProgress === 'function') {
|
||||
try {
|
||||
onProgress(detail);
|
||||
} catch (error) {
|
||||
console.error('[extensionReimportBridge] onProgress callback failed:', error);
|
||||
}
|
||||
}
|
||||
};
|
||||
const onBatchDone = (event) => {
|
||||
const detail = parseDetail(event);
|
||||
if (!detail || detail.requestId !== requestId) return;
|
||||
succeed({
|
||||
completed: Number.isInteger(detail.completed) ? detail.completed : 0,
|
||||
failed: Number.isInteger(detail.failed) ? detail.failed : 0,
|
||||
});
|
||||
};
|
||||
|
||||
document.addEventListener(PROGRESS_EVENT, onProgressEvent);
|
||||
document.addEventListener(BATCH_DONE_EVENT, onBatchDone);
|
||||
armTimer();
|
||||
dispatchProtocolEvent(REIMPORT_EVENT, { requestId, recipes });
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Extract CivitAI image page info from a recipe source_path.
|
||||
* Mirrors py/utils/civitai_utils.py `extract_civitai_image_id`.
|
||||
*
|
||||
* @param {string|null} sourcePath - Recipe source_path.
|
||||
* @returns {{imageId: number, imageUrl: string}|null} Null when the path is
|
||||
* not a `/images/<id>` URL on civitai.com/.red/.green.
|
||||
*/
|
||||
export function getCivitaiImageInfo(sourcePath) {
|
||||
if (!sourcePath || typeof sourcePath !== 'string') {
|
||||
return null;
|
||||
}
|
||||
|
||||
let parsed;
|
||||
try {
|
||||
parsed = new URL(sourcePath);
|
||||
} catch {
|
||||
return null;
|
||||
}
|
||||
|
||||
if (parsed.protocol !== 'http:' && parsed.protocol !== 'https:') {
|
||||
return null;
|
||||
}
|
||||
if (!SUPPORTED_CIVITAI_PAGE_HOSTS.has(parsed.hostname.toLowerCase())) {
|
||||
return null;
|
||||
}
|
||||
|
||||
const pathMatch = parsed.pathname.match(/\/images\/(\d+)/);
|
||||
if (!pathMatch) {
|
||||
return null;
|
||||
}
|
||||
|
||||
return { imageId: Number(pathMatch[1]), imageUrl: sourcePath };
|
||||
}
|
||||
@@ -94,9 +94,6 @@
|
||||
<div class="context-menu-item" data-action="check-updates">
|
||||
<i class="fas fa-bell"></i> <span>{{ t('loras.bulkOperations.checkUpdates') }}</span>
|
||||
</div>
|
||||
<div class="context-menu-item" data-action="repair-metadata">
|
||||
<i class="fas fa-tools"></i> <span>{{ t('loras.bulkOperations.repairMetadata') }}</span> (Deprecated)
|
||||
</div>
|
||||
<div class="context-menu-item" data-action="rematch-metadata">
|
||||
<i class="fas fa-link"></i> <span>{{ t('loras.bulkOperations.rematchMetadata') }}</span>
|
||||
</div>
|
||||
@@ -202,9 +199,6 @@
|
||||
<i class="fas fa-layer-group"></i> <span>{{ t('globalContextMenu.groupByModel.label') }}</span>
|
||||
<i class="fas fa-check check-indicator" style="margin-left:auto;display:none"></i>
|
||||
</div>
|
||||
<div class="context-menu-item" data-action="repair-recipes">
|
||||
<i class="fas fa-tools"></i> <span>{{ t('globalContextMenu.repairRecipes.label') }}</span> (Deprecated)
|
||||
</div>
|
||||
<div class="context-menu-item" data-action="rematch-recipes">
|
||||
<i class="fas fa-link"></i> <span>{{ t('globalContextMenu.rematchRecipes.label') }}</span>
|
||||
</div>
|
||||
|
||||
@@ -18,9 +18,6 @@
|
||||
<div id="recipeContextMenu" class="context-menu" style="display: none;">
|
||||
<!-- <div class="context-menu-item" data-action="details"><i class="fas fa-info-circle"></i> View Details</div> -->
|
||||
<!-- Metadata -->
|
||||
<div class="context-menu-item" data-action="repair">
|
||||
<i class="fas fa-tools"></i> {{ t('loras.contextMenu.repairMetadata') }} (Deprecated)
|
||||
</div>
|
||||
<div class="context-menu-item" data-action="rematch">
|
||||
<i class="fas fa-link"></i> {{ t('loras.contextMenu.rematchMetadata') }}
|
||||
</div>
|
||||
|
||||
@@ -0,0 +1,181 @@
|
||||
import { describe, it, beforeEach, afterEach, expect, vi } from 'vitest';
|
||||
|
||||
const showToastMock = vi.fn();
|
||||
const showSimpleLoadingMock = vi.fn();
|
||||
const hideLoadingMock = vi.fn();
|
||||
const resetAndReloadMock = vi.fn();
|
||||
const probeExtensionMock = vi.fn();
|
||||
const delegateReimportMock = vi.fn();
|
||||
|
||||
const stateStub = {
|
||||
virtualScroller: { items: [] },
|
||||
loadingManager: {
|
||||
showSimpleLoading: showSimpleLoadingMock,
|
||||
hide: hideLoadingMock,
|
||||
},
|
||||
};
|
||||
|
||||
vi.mock('../../../static/js/utils/uiHelpers.js', () => ({
|
||||
showToast: showToastMock,
|
||||
copyToClipboard: vi.fn(),
|
||||
sendLoraToWorkflow: vi.fn(),
|
||||
}));
|
||||
|
||||
vi.mock('../../../static/js/utils/storageHelpers.js', () => ({
|
||||
setSessionItem: vi.fn(),
|
||||
removeSessionItem: vi.fn(),
|
||||
}));
|
||||
|
||||
vi.mock('../../../static/js/api/recipeApi.js', () => ({
|
||||
updateRecipeMetadata: vi.fn(),
|
||||
resetAndReload: resetAndReloadMock,
|
||||
}));
|
||||
|
||||
vi.mock('../../../static/js/state/index.js', () => ({
|
||||
state: stateStub,
|
||||
}));
|
||||
|
||||
vi.mock('../../../static/js/managers/MoveManager.js', () => ({
|
||||
moveManager: { showMoveModal: vi.fn() },
|
||||
}));
|
||||
|
||||
vi.mock('../../../static/js/components/ContextMenu/ModelContextMenuMixin.js', () => ({
|
||||
ModelContextMenuMixin: {
|
||||
handleCommonMenuActions: vi.fn(() => false),
|
||||
initNSFWSelector: vi.fn(),
|
||||
},
|
||||
}));
|
||||
|
||||
// Keep the real getCivitaiImageInfo (gating logic under test); mock only the
|
||||
// extension communication.
|
||||
vi.mock('../../../static/js/utils/extensionReimportBridge.js', async (importOriginal) => {
|
||||
const actual = await importOriginal();
|
||||
return {
|
||||
...actual,
|
||||
probeExtension: probeExtensionMock,
|
||||
delegateReimport: delegateReimportMock,
|
||||
};
|
||||
});
|
||||
|
||||
describe('RecipeContextMenu.reimportRecipe extension delegation', () => {
|
||||
beforeEach(() => {
|
||||
vi.clearAllMocks();
|
||||
document.body.innerHTML = `
|
||||
<div id="recipeContextMenu" class="context-menu" style="display: none;">
|
||||
<div class="context-menu-item" data-action="reimport"></div>
|
||||
</div>
|
||||
`;
|
||||
stateStub.virtualScroller.items = [
|
||||
{
|
||||
id: 'recipe-1',
|
||||
file_path: '/recipes/recipe-1.webp',
|
||||
title: 'Civitai Recipe',
|
||||
source_path: 'https://civitai.com/images/12345',
|
||||
},
|
||||
{
|
||||
id: 'recipe-2',
|
||||
file_path: '/recipes/recipe-2.webp',
|
||||
title: 'Local Recipe',
|
||||
source_path: '/data/imports/local.png',
|
||||
},
|
||||
];
|
||||
global.fetch = vi.fn().mockResolvedValue({
|
||||
ok: true,
|
||||
json: async () => ({ success: true, recipe_id: 'new-id', loras_count: 2 }),
|
||||
});
|
||||
});
|
||||
|
||||
afterEach(() => {
|
||||
delete global.fetch;
|
||||
});
|
||||
|
||||
async function createMenu() {
|
||||
const { RecipeContextMenu } = await import(
|
||||
'../../../static/js/components/ContextMenu/RecipeContextMenu.js'
|
||||
);
|
||||
return new RecipeContextMenu();
|
||||
}
|
||||
|
||||
it('delegates to the extension for a CivitAI image source when licensed', async () => {
|
||||
probeExtensionMock.mockResolvedValue({ supported: true, licenseValid: true });
|
||||
delegateReimportMock.mockResolvedValue({ completed: 1, failed: 0 });
|
||||
|
||||
const menu = await createMenu();
|
||||
await menu.reimportRecipe('recipe-1');
|
||||
|
||||
expect(delegateReimportMock).toHaveBeenCalledWith([{
|
||||
recipeId: 'recipe-1',
|
||||
imageId: 12345,
|
||||
imageUrl: 'https://civitai.com/images/12345',
|
||||
title: 'Civitai Recipe',
|
||||
}]);
|
||||
expect(global.fetch).not.toHaveBeenCalled();
|
||||
expect(showToastMock).toHaveBeenCalledWith('toast.recipes.reimportSuccess', {}, 'success');
|
||||
expect(resetAndReloadMock).toHaveBeenCalledWith(false, { preserveScroll: false });
|
||||
});
|
||||
|
||||
it('shows the failure toast when the extension reports failures', async () => {
|
||||
probeExtensionMock.mockResolvedValue({ supported: true, licenseValid: true });
|
||||
delegateReimportMock.mockResolvedValue({ completed: 0, failed: 1 });
|
||||
|
||||
const menu = await createMenu();
|
||||
await menu.reimportRecipe('recipe-1');
|
||||
|
||||
expect(showToastMock).toHaveBeenCalledWith(
|
||||
'recipes.contextMenu.reimport.failed',
|
||||
{ message: 'Extension re-import failed' },
|
||||
'error'
|
||||
);
|
||||
expect(global.fetch).not.toHaveBeenCalled();
|
||||
expect(resetAndReloadMock).toHaveBeenCalledWith(false, { preserveScroll: false });
|
||||
});
|
||||
|
||||
it('uses the native path for non-CivitAI sources without probing', async () => {
|
||||
const menu = await createMenu();
|
||||
await menu.reimportRecipe('recipe-2');
|
||||
|
||||
expect(probeExtensionMock).not.toHaveBeenCalled();
|
||||
expect(delegateReimportMock).not.toHaveBeenCalled();
|
||||
expect(global.fetch).toHaveBeenCalledWith('/api/lm/recipe/recipe-2/reimport', {
|
||||
method: 'POST',
|
||||
});
|
||||
expect(showToastMock).toHaveBeenCalledWith('toast.recipes.reimportSuccess', {}, 'success');
|
||||
});
|
||||
|
||||
it('uses the native path when the extension is absent (probe timeout)', async () => {
|
||||
probeExtensionMock.mockResolvedValue(null);
|
||||
|
||||
const menu = await createMenu();
|
||||
await menu.reimportRecipe('recipe-1');
|
||||
|
||||
expect(delegateReimportMock).not.toHaveBeenCalled();
|
||||
expect(global.fetch).toHaveBeenCalledWith('/api/lm/recipe/recipe-1/reimport', {
|
||||
method: 'POST',
|
||||
});
|
||||
});
|
||||
|
||||
it('uses the native path when the license is invalid', async () => {
|
||||
probeExtensionMock.mockResolvedValue({ supported: true, licenseValid: false });
|
||||
|
||||
const menu = await createMenu();
|
||||
await menu.reimportRecipe('recipe-1');
|
||||
|
||||
expect(delegateReimportMock).not.toHaveBeenCalled();
|
||||
expect(global.fetch).toHaveBeenCalledWith('/api/lm/recipe/recipe-1/reimport', {
|
||||
method: 'POST',
|
||||
});
|
||||
});
|
||||
|
||||
it('falls back to the native path when delegation fails', async () => {
|
||||
probeExtensionMock.mockResolvedValue({ supported: true, licenseValid: true });
|
||||
delegateReimportMock.mockRejectedValue(new Error('Extension re-import timed out'));
|
||||
|
||||
const menu = await createMenu();
|
||||
await menu.reimportRecipe('recipe-1');
|
||||
|
||||
expect(global.fetch).toHaveBeenCalledWith('/api/lm/recipe/recipe-1/reimport', {
|
||||
method: 'POST',
|
||||
});
|
||||
expect(showToastMock).toHaveBeenCalledWith('toast.recipes.reimportSuccess', {}, 'success');
|
||||
});
|
||||
});
|
||||
@@ -153,6 +153,16 @@ const hashInvalidLora = {
|
||||
hashInvalid: true,
|
||||
};
|
||||
|
||||
// Mirrors the shape served for page-imported recipes whose CivitAI version
|
||||
// exposes no sha256: an exact modelVersionId but no modelId and no hash.
|
||||
const versionOnlyLora = {
|
||||
name: 'version-lora',
|
||||
modelName: 'Version Only LoRA',
|
||||
inLibrary: false,
|
||||
modelVersionId: 3221586,
|
||||
modelVersionName: 'V1 KREA-2',
|
||||
};
|
||||
|
||||
const recipeWithResources = {
|
||||
id: 'recipe-resources',
|
||||
file_path: '/recipes/resources.json',
|
||||
@@ -171,6 +181,7 @@ const recipeWithResources = {
|
||||
hashInvalidLora,
|
||||
{ name: 'mystery-lora', modelName: 'Mystery LoRA', inLibrary: false },
|
||||
hashOnlyLora,
|
||||
versionOnlyLora,
|
||||
],
|
||||
};
|
||||
|
||||
@@ -281,6 +292,57 @@ describe('RecipeModal resource item interactions', () => {
|
||||
);
|
||||
});
|
||||
|
||||
it('renders a download action (not reconnect) for a version-only LoRA', async () => {
|
||||
const recipeModal = await createRecipeModal();
|
||||
recipeModal.showRecipeDetails(recipeWithResources);
|
||||
await flushWiring();
|
||||
|
||||
const item = document.querySelector('[data-lora-index="6"]');
|
||||
expect(item).not.toBeNull();
|
||||
expect(item.classList.contains('missing-locally')).toBe(true);
|
||||
// Missing from the local library (badge) but still downloadable by its
|
||||
// exact CivitAI version id, so the row offers Download, not Reconnect.
|
||||
expect(item.querySelector('.missing-badge')).not.toBeNull();
|
||||
expect(item.querySelector('.lora-download')).not.toBeNull();
|
||||
expect(item.querySelector('.lora-reconnect')).toBeNull();
|
||||
});
|
||||
|
||||
it('downloads a version-only LoRA by resolving the model id from the version endpoint', async () => {
|
||||
const recipeModal = await createRecipeModal();
|
||||
const requests = [];
|
||||
// Isolated copy keeps mutations out of the shared fixture.
|
||||
const isolatedRecipe = JSON.parse(JSON.stringify(recipeWithResources));
|
||||
fetchRecipeDetailsMock.mockResolvedValue(isolatedRecipe);
|
||||
global.fetch = vi.fn(async (url) => {
|
||||
requests.push(String(url));
|
||||
if (String(url).includes('/civitai/model/version/3221586')) {
|
||||
return {
|
||||
ok: true,
|
||||
json: async () => ({ id: 3221586, modelId: 56789, name: 'V1 KREA-2' }),
|
||||
};
|
||||
}
|
||||
return { ok: true, json: async () => ({}) };
|
||||
});
|
||||
recipeModal.showRecipeDetails(isolatedRecipe);
|
||||
await flushWiring();
|
||||
|
||||
const item = document.querySelector('[data-lora-index="6"]');
|
||||
item.querySelector('.lora-download').click();
|
||||
|
||||
await vi.waitFor(() => {
|
||||
expect(downloadVersionWithDefaultsMock).toHaveBeenCalledTimes(1);
|
||||
});
|
||||
expect(
|
||||
requests.some(u => u.includes('/civitai/model/version/3221586'))
|
||||
).toBe(true);
|
||||
expect(downloadVersionWithDefaultsMock).toHaveBeenCalledWith(
|
||||
'loras',
|
||||
56789,
|
||||
3221586,
|
||||
expect.objectContaining({ source: 'recipe-modal' })
|
||||
);
|
||||
});
|
||||
|
||||
it('does not navigate when a missing LoRA row is clicked', async () => {
|
||||
const recipeModal = await createRecipeModal();
|
||||
const navigateSpy = vi
|
||||
|
||||
@@ -0,0 +1,216 @@
|
||||
import { describe, it, expect, vi, afterEach } from 'vitest';
|
||||
|
||||
import {
|
||||
probeExtension,
|
||||
delegateReimport,
|
||||
getCivitaiImageInfo,
|
||||
} from '../../../static/js/utils/extensionReimportBridge.js';
|
||||
|
||||
const dispatchedEvents = [];
|
||||
|
||||
function dispatchProtocolEvent(type, payload) {
|
||||
document.dispatchEvent(
|
||||
new CustomEvent(type, { detail: JSON.stringify(payload) })
|
||||
);
|
||||
}
|
||||
|
||||
// Installs a fake extension that answers probes with the given result.
|
||||
function installProbeResponder(result) {
|
||||
const listener = () => dispatchProtocolEvent('lm:reimportProbeResult', result);
|
||||
document.addEventListener('lm:reimportProbe', listener);
|
||||
return () => document.removeEventListener('lm:reimportProbe', listener);
|
||||
}
|
||||
|
||||
afterEach(() => {
|
||||
dispatchedEvents.length = 0;
|
||||
});
|
||||
|
||||
describe('probeExtension', () => {
|
||||
it('resolves null when no extension answers within the timeout', async () => {
|
||||
const result = await probeExtension({ timeoutMs: 20 });
|
||||
expect(result).toBeNull();
|
||||
});
|
||||
|
||||
it('resolves the probe result when the extension answers', async () => {
|
||||
const uninstall = installProbeResponder({
|
||||
supported: true,
|
||||
licenseValid: true,
|
||||
extensionVersion: '1.2.3',
|
||||
});
|
||||
try {
|
||||
const result = await probeExtension({ timeoutMs: 1000 });
|
||||
expect(result).toEqual({
|
||||
supported: true,
|
||||
licenseValid: true,
|
||||
extensionVersion: '1.2.3',
|
||||
reason: undefined,
|
||||
});
|
||||
} finally {
|
||||
uninstall();
|
||||
}
|
||||
});
|
||||
|
||||
it('reports unsupported/unlicensed answers verbatim', async () => {
|
||||
const uninstall = installProbeResponder({
|
||||
supported: false,
|
||||
licenseValid: false,
|
||||
reason: 'license expired',
|
||||
});
|
||||
try {
|
||||
const result = await probeExtension({ timeoutMs: 1000 });
|
||||
expect(result.supported).toBe(false);
|
||||
expect(result.licenseValid).toBe(false);
|
||||
expect(result.reason).toBe('license expired');
|
||||
} finally {
|
||||
uninstall();
|
||||
}
|
||||
});
|
||||
|
||||
it('ignores malformed probe results and times out', async () => {
|
||||
const listener = () => {
|
||||
document.dispatchEvent(
|
||||
new CustomEvent('lm:reimportProbeResult', { detail: '{broken json' })
|
||||
);
|
||||
};
|
||||
document.addEventListener('lm:reimportProbe', listener);
|
||||
try {
|
||||
const result = await probeExtension({ timeoutMs: 20 });
|
||||
expect(result).toBeNull();
|
||||
} finally {
|
||||
document.removeEventListener('lm:reimportProbe', listener);
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
describe('delegateReimport', () => {
|
||||
const recipes = [
|
||||
{ recipeId: 'r1', imageId: 123, imageUrl: 'https://civitai.com/images/123', title: 'One' },
|
||||
{ recipeId: 'r2', imageId: 456, imageUrl: 'https://civitai.com/images/456', title: 'Two' },
|
||||
];
|
||||
|
||||
it('rejects immediately for an empty recipe list', async () => {
|
||||
await expect(delegateReimport([])).rejects.toThrow('non-empty');
|
||||
});
|
||||
|
||||
it('rejects on timeout when the extension never answers', async () => {
|
||||
await expect(
|
||||
delegateReimport(recipes, { timeoutMs: 20 })
|
||||
).rejects.toThrow('timed out');
|
||||
});
|
||||
|
||||
it('dispatches the batch with a requestId and resolves on batchDone', async () => {
|
||||
const progressEvents = [];
|
||||
let seenRequest = null;
|
||||
|
||||
const listener = (event) => {
|
||||
seenRequest = JSON.parse(event.detail);
|
||||
const { requestId } = seenRequest;
|
||||
// Progress for a DIFFERENT batch must be ignored.
|
||||
dispatchProtocolEvent('lm:reimportProgress', {
|
||||
requestId: 'other-batch',
|
||||
current: 99,
|
||||
total: 99,
|
||||
recipeId: 'nope',
|
||||
title: 'nope',
|
||||
status: 'success',
|
||||
});
|
||||
dispatchProtocolEvent('lm:reimportProgress', {
|
||||
requestId,
|
||||
current: 1,
|
||||
total: 2,
|
||||
recipeId: 'r1',
|
||||
title: 'One',
|
||||
status: 'success',
|
||||
});
|
||||
dispatchProtocolEvent('lm:reimportProgress', {
|
||||
requestId,
|
||||
current: 2,
|
||||
total: 2,
|
||||
recipeId: 'r2',
|
||||
title: 'Two',
|
||||
status: 'failed',
|
||||
message: 'boom',
|
||||
});
|
||||
dispatchProtocolEvent('lm:reimportBatchDone', {
|
||||
requestId,
|
||||
completed: 1,
|
||||
failed: 1,
|
||||
});
|
||||
};
|
||||
document.addEventListener('lm:reimportViaExtension', listener);
|
||||
try {
|
||||
const result = await delegateReimport(recipes, {
|
||||
onProgress: (progress) => progressEvents.push(progress),
|
||||
timeoutMs: 1000,
|
||||
});
|
||||
|
||||
expect(seenRequest.recipes).toEqual(recipes);
|
||||
expect(typeof seenRequest.requestId).toBe('string');
|
||||
expect(seenRequest.requestId.length).toBeGreaterThan(0);
|
||||
expect(result).toEqual({ completed: 1, failed: 1 });
|
||||
// Only this batch's progress events reach the callback.
|
||||
expect(progressEvents.map((p) => p.recipeId)).toEqual(['r1', 'r2']);
|
||||
expect(progressEvents[1].status).toBe('failed');
|
||||
} finally {
|
||||
document.removeEventListener('lm:reimportViaExtension', listener);
|
||||
}
|
||||
});
|
||||
|
||||
it('resets the timeout on every progress heartbeat', async () => {
|
||||
vi.useFakeTimers();
|
||||
let requestId = null;
|
||||
const listener = (event) => {
|
||||
requestId = JSON.parse(event.detail).requestId;
|
||||
};
|
||||
document.addEventListener('lm:reimportViaExtension', listener);
|
||||
try {
|
||||
const promise = delegateReimport(recipes, { timeoutMs: 1000 });
|
||||
|
||||
// At t=900ms a progress event arrives, pushing the deadline to t=1900ms.
|
||||
await vi.advanceTimersByTimeAsync(900);
|
||||
dispatchProtocolEvent('lm:reimportProgress', {
|
||||
requestId,
|
||||
current: 1,
|
||||
total: 2,
|
||||
recipeId: 'r1',
|
||||
title: 'One',
|
||||
status: 'started',
|
||||
});
|
||||
// t=1800ms: past the original deadline, still alive thanks to heartbeat.
|
||||
await vi.advanceTimersByTimeAsync(900);
|
||||
dispatchProtocolEvent('lm:reimportBatchDone', {
|
||||
requestId,
|
||||
completed: 2,
|
||||
failed: 0,
|
||||
});
|
||||
|
||||
await expect(promise).resolves.toEqual({ completed: 2, failed: 0 });
|
||||
} finally {
|
||||
document.removeEventListener('lm:reimportViaExtension', listener);
|
||||
vi.useRealTimers();
|
||||
}
|
||||
});
|
||||
});
|
||||
|
||||
describe('getCivitaiImageInfo', () => {
|
||||
it.each([
|
||||
'https://civitai.com/images/12345',
|
||||
'https://civitai.red/images/12345',
|
||||
'https://civitai.green/images/12345',
|
||||
'https://civitai.com/images/12345?foo=bar',
|
||||
])('extracts the image id from %s', (url) => {
|
||||
expect(getCivitaiImageInfo(url)).toEqual({ imageId: 12345, imageUrl: url });
|
||||
});
|
||||
|
||||
it.each([
|
||||
null,
|
||||
'',
|
||||
'not a url',
|
||||
'ftp://civitai.com/images/12345',
|
||||
'https://civitai.com/models/12345',
|
||||
'https://example.com/images/12345',
|
||||
'https://image.civitai.com/x/y/original=true/pic.png',
|
||||
])('returns null for %s', (url) => {
|
||||
expect(getCivitaiImageInfo(url)).toBeNull();
|
||||
});
|
||||
});
|
||||
@@ -42,7 +42,6 @@ def sample_recipe_data() -> Dict[str, Any]:
|
||||
"created_date": 1700000000.0,
|
||||
"modified": 1700000100.0,
|
||||
"favorite": False,
|
||||
"repair_version": 1,
|
||||
"preview_nsfw_level": 0,
|
||||
"loras": [
|
||||
{"hash": "lora1hash", "file_name": "test_lora1", "strength": 0.8},
|
||||
|
||||
@@ -226,15 +226,6 @@ _REMATCH_ROUTE_DEFS = {
|
||||
("GET", "/api/lm/recipes/rematch-progress", "get_rematch_progress"),
|
||||
}
|
||||
|
||||
_REPAIR_ROUTE_DEFS = {
|
||||
("POST", "/api/lm/recipes/repair", "repair_recipes"),
|
||||
("POST", "/api/lm/recipes/cancel-repair", "cancel_repair"),
|
||||
("POST", "/api/lm/recipe/{recipe_id}/repair", "repair_recipe"),
|
||||
("POST", "/api/lm/recipes/repair-bulk", "repair_recipes_bulk"),
|
||||
("GET", "/api/lm/recipes/repair-progress", "get_repair_progress"),
|
||||
}
|
||||
|
||||
|
||||
def test_rematch_route_definitions_registered():
|
||||
registered = {
|
||||
(d.method, d.path, d.handler_name)
|
||||
@@ -243,14 +234,6 @@ def test_rematch_route_definitions_registered():
|
||||
assert _REMATCH_ROUTE_DEFS <= registered
|
||||
|
||||
|
||||
def test_repair_route_definitions_still_registered():
|
||||
registered = {
|
||||
(d.method, d.path, d.handler_name)
|
||||
for d in recipe_route_registrar.ROUTE_DEFINITIONS
|
||||
}
|
||||
assert _REPAIR_ROUTE_DEFS <= registered
|
||||
|
||||
|
||||
def test_rematch_handler_names_resolve_in_to_route_mapping(monkeypatch: pytest.MonkeyPatch):
|
||||
"""Oracle R1-F4: register_routes KeyErrors at startup if to_route_mapping
|
||||
lacks any name present in ROUTE_DEFINITIONS, so the real handler set must
|
||||
|
||||
@@ -1874,20 +1874,14 @@ async def test_create_from_example_does_not_recompute_stored_autov3(
|
||||
def _clean_recipe_run_progress_state():
|
||||
"""Keep the shared WS manager run-state isolated between tests."""
|
||||
ws_manager._recipe_rematch_progress = None
|
||||
ws_manager._recipe_repair_progress = None
|
||||
yield
|
||||
ws_manager._recipe_rematch_progress = None
|
||||
ws_manager._recipe_repair_progress = None
|
||||
|
||||
|
||||
def _set_rematch_running(status: str = "processing") -> None:
|
||||
ws_manager._recipe_rematch_progress = {"status": status}
|
||||
|
||||
|
||||
def _set_repair_running(status: str = "processing") -> None:
|
||||
ws_manager._recipe_repair_progress = {"status": status}
|
||||
|
||||
|
||||
async def test_rematch_recipes_starts_background_run(monkeypatch, tmp_path: Path) -> None:
|
||||
async with recipe_harness(monkeypatch, tmp_path) as harness:
|
||||
response = await harness.client.post("/api/lm/recipes/rematch")
|
||||
@@ -1911,15 +1905,6 @@ async def test_rematch_recipes_409_when_rematch_running(monkeypatch, tmp_path: P
|
||||
assert "already in progress" in payload["error"].lower()
|
||||
|
||||
|
||||
async def test_rematch_recipes_409_when_repair_running(monkeypatch, tmp_path: Path) -> None:
|
||||
async with recipe_harness(monkeypatch, tmp_path) as harness:
|
||||
_set_repair_running()
|
||||
response = await harness.client.post("/api/lm/recipes/rematch")
|
||||
payload = await response.json()
|
||||
assert response.status == 409
|
||||
assert payload["success"] is False
|
||||
assert "already in progress" in payload["error"].lower()
|
||||
|
||||
|
||||
async def test_rematch_recipe_409_when_rematch_running(monkeypatch, tmp_path: Path) -> None:
|
||||
async with recipe_harness(monkeypatch, tmp_path) as harness:
|
||||
@@ -2356,3 +2341,147 @@ async def test_get_recipe_detail_includes_recipe_json_path(
|
||||
assert response.status == 200
|
||||
payload = await response.json()
|
||||
assert "recipe_json_path" not in payload
|
||||
|
||||
|
||||
async def test_reimport_with_extension_payload_uses_payload_path(
|
||||
monkeypatch, tmp_path: Path
|
||||
) -> None:
|
||||
"""A re-import carrying the companion extension's metadata payload must
|
||||
use the payload-based import engine (caller-supplied LoRAs) instead of
|
||||
the legacy CivitAI image URL import, and report loras_count."""
|
||||
provider_calls: list[str | int] = []
|
||||
|
||||
class Provider:
|
||||
async def get_model_version_info(self, model_version_id):
|
||||
provider_calls.append(model_version_id)
|
||||
return {}, None
|
||||
|
||||
async def fake_get_default_metadata_provider():
|
||||
return Provider()
|
||||
|
||||
monkeypatch.setattr(
|
||||
"py.recipes.enrichment.get_default_metadata_provider",
|
||||
fake_get_default_metadata_provider,
|
||||
)
|
||||
|
||||
async with recipe_harness(monkeypatch, tmp_path) as harness:
|
||||
old_file = harness.tmp_dir / "recipes" / "sub" / "rec-ext.webp"
|
||||
harness.scanner.recipes["rec-ext"] = {
|
||||
"id": "rec-ext",
|
||||
"title": "Old title",
|
||||
"file_path": str(old_file),
|
||||
"tags": ["tag1"],
|
||||
"source_path": "https://civitai.com/images/12345",
|
||||
}
|
||||
harness.civitai.image_info["12345"] = {
|
||||
"id": 12345,
|
||||
"url": "https://image.civitai.com/x/y/original=true/pic.png",
|
||||
"type": "image",
|
||||
}
|
||||
harness.persistence.save_result = SimpleNamespace(
|
||||
payload={"success": True, "recipe_id": "new-rec-ext"}, status=200
|
||||
)
|
||||
# The freshly saved recipe as the scanner would see it (for loras_count).
|
||||
harness.scanner.recipes["new-rec-ext"] = {
|
||||
"id": "new-rec-ext",
|
||||
"loras": [{"file_name": "Painterly"}],
|
||||
}
|
||||
|
||||
resources = [
|
||||
{
|
||||
"type": "lora",
|
||||
"modelId": 20,
|
||||
"modelVersionId": 44,
|
||||
"modelName": "Painterly",
|
||||
"modelVersionName": "v2",
|
||||
"weight": 0.5,
|
||||
},
|
||||
]
|
||||
# The extension only issues GET requests (per its API convention).
|
||||
response = await harness.client.get(
|
||||
"/api/lm/recipe/rec-ext/reimport",
|
||||
params={
|
||||
"image_url": "https://civitai.com/images/12345",
|
||||
"name": "Extension Recipe",
|
||||
"resources": json.dumps(resources),
|
||||
"gen_params": json.dumps({"prompt": "from extension"}),
|
||||
"base_model": "Flux",
|
||||
},
|
||||
)
|
||||
payload = await response.json()
|
||||
|
||||
assert response.status == 200
|
||||
assert payload["success"] is True
|
||||
assert payload["old_recipe_id"] == "rec-ext"
|
||||
assert payload["recipe_id"] == "new-rec-ext"
|
||||
assert payload["loras_count"] == 1
|
||||
|
||||
save_call = harness.persistence.save_calls[-1]
|
||||
# Caller-supplied payload data wins: name, LoRAs, gen params.
|
||||
assert save_call["name"] == "Extension Recipe"
|
||||
assert save_call["metadata"]["loras"][0]["file_name"] == "Painterly"
|
||||
assert save_call["metadata"]["loras"][0]["weight"] == 0.5
|
||||
assert save_call["metadata"]["gen_params"]["prompt"] == "from extension"
|
||||
# Reimport semantics: original source_path and folder are preserved.
|
||||
assert save_call["metadata"]["source_path"] == "https://civitai.com/images/12345"
|
||||
assert save_call["target_dir"] == str(harness.tmp_dir / "recipes" / "sub")
|
||||
# The old recipe is deleted and user edits carried over.
|
||||
assert harness.persistence.delete_calls == ["rec-ext"]
|
||||
assert harness.persistence.update_calls[-1]["recipe_id"] == "new-rec-ext"
|
||||
assert harness.persistence.update_calls[-1]["updates"]["title"] == "Old title"
|
||||
assert harness.persistence.update_calls[-1]["updates"]["tags"] == ["tag1"]
|
||||
|
||||
|
||||
async def test_reimport_with_malformed_payload_falls_back_to_legacy(
|
||||
monkeypatch, tmp_path: Path
|
||||
) -> None:
|
||||
"""Malformed resources JSON must be treated as "no payload": the legacy
|
||||
source-URL import runs and the request still succeeds."""
|
||||
async def fake_get_default_metadata_provider():
|
||||
return SimpleNamespace(get_model_version_info=lambda id: ({}, None))
|
||||
|
||||
monkeypatch.setattr(
|
||||
"py.recipes.enrichment.get_default_metadata_provider",
|
||||
fake_get_default_metadata_provider,
|
||||
)
|
||||
|
||||
async with recipe_harness(monkeypatch, tmp_path) as harness:
|
||||
harness.scanner.recipes["rec-bad"] = {
|
||||
"id": "rec-bad",
|
||||
"title": "Broken payload",
|
||||
"file_path": str(harness.tmp_dir / "recipes" / "rec-bad.webp"),
|
||||
"tags": [],
|
||||
"source_path": "https://civitai.com/images/12345",
|
||||
}
|
||||
harness.civitai.image_info["12345"] = {
|
||||
"id": 12345,
|
||||
"url": "https://image.civitai.com/x/y/original=true/pic.png",
|
||||
"type": "image",
|
||||
}
|
||||
harness.persistence.save_result = SimpleNamespace(
|
||||
payload={"success": True, "recipe_id": "legacy-new"}, status=200
|
||||
)
|
||||
harness.scanner.recipes["legacy-new"] = {"id": "legacy-new", "loras": []}
|
||||
|
||||
response = await harness.client.get(
|
||||
"/api/lm/recipe/rec-bad/reimport",
|
||||
params={
|
||||
"image_url": "https://civitai.com/images/12345",
|
||||
"name": "Ignored Name",
|
||||
"resources": "{not valid json",
|
||||
},
|
||||
)
|
||||
payload = await response.json()
|
||||
|
||||
assert response.status == 200
|
||||
assert payload["success"] is True
|
||||
assert payload["recipe_id"] == "legacy-new"
|
||||
assert payload["loras_count"] == 0
|
||||
|
||||
save_call = harness.persistence.save_calls[-1]
|
||||
# Legacy URL path: the payload name is ignored and the title is
|
||||
# derived from the (empty) metadata, and no caller LoRAs are used.
|
||||
assert save_call["name"] == "Civitai Image 12345"
|
||||
assert save_call["metadata"]["loras"] == []
|
||||
assert save_call["metadata"]["source_path"] == "https://civitai.com/images/12345"
|
||||
assert harness.persistence.delete_calls == ["rec-bad"]
|
||||
|
||||
@@ -818,3 +818,44 @@ async def test_get_model_by_hash_rejects_empty_placeholder_without_request(downl
|
||||
assert result is None
|
||||
assert error == "Model not found"
|
||||
assert requested == []
|
||||
|
||||
|
||||
async def test_get_version_file_mini_returns_payload(downloader):
|
||||
"""The mini endpoint returns the raw stored filename (#1100)."""
|
||||
client = await CivitaiClient.get_instance()
|
||||
|
||||
async def fake_make_request(method, url, use_auth=True, **kwargs):
|
||||
assert method == "GET"
|
||||
assert url.endswith("/model-versions/mini/3284136")
|
||||
assert kwargs.get("params") == {"modelFileId": 3168412}
|
||||
assert use_auth is True
|
||||
return True, {"fileName": "CyberRealistic_zit_v8.0_bf16.safetensors"}
|
||||
|
||||
downloader.make_request = fake_make_request
|
||||
|
||||
result = await client.get_version_file_mini(3284136, 3168412)
|
||||
|
||||
assert result == {"fileName": "CyberRealistic_zit_v8.0_bf16.safetensors"}
|
||||
|
||||
|
||||
async def test_get_version_file_mini_returns_none_on_failure(downloader):
|
||||
client = await CivitaiClient.get_instance()
|
||||
|
||||
async def fake_make_request(method, url, use_auth=True, **kwargs):
|
||||
return False, "Model file 2 not found in version 1"
|
||||
|
||||
downloader.make_request = fake_make_request
|
||||
|
||||
assert await client.get_version_file_mini(1, 2) is None
|
||||
|
||||
|
||||
async def test_get_version_file_mini_propagates_rate_limit(downloader):
|
||||
client = await CivitaiClient.get_instance()
|
||||
|
||||
async def fake_make_request(method, url, use_auth=True, **kwargs):
|
||||
return False, RateLimitError("limited", retry_after=1.0)
|
||||
|
||||
downloader.make_request = fake_make_request
|
||||
|
||||
with pytest.raises(RateLimitError):
|
||||
await client.get_version_file_mini(1, 2)
|
||||
|
||||
@@ -2098,3 +2098,174 @@ async def test_discard_cleared_downloads_stops_tracking_and_preserves_files(
|
||||
# Partial files are preserved for a future resume from disk.
|
||||
assert save_path.exists()
|
||||
assert control_path.exists()
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_download_uses_raw_file_name_from_mini_endpoint(
|
||||
monkeypatch, scanners, metadata_provider, tmp_path
|
||||
):
|
||||
"""#1100: when the REST name is rewritten ("{model}_{version}"), the raw
|
||||
stored filename from the mini endpoint wins for the on-disk name."""
|
||||
manager = DownloadManager()
|
||||
get_settings_manager().settings["default_unet_root"] = str(tmp_path / "unet")
|
||||
metadata_provider.payload = {
|
||||
"id": 3284136,
|
||||
"model": {"type": "Checkpoint", "tags": ["realistic"]},
|
||||
"baseModel": "ZImageTurbo",
|
||||
"creator": {"username": "Author"},
|
||||
"files": [
|
||||
{
|
||||
"id": 3168412,
|
||||
"type": "Model",
|
||||
"primary": True,
|
||||
"name": "cyberrealisticZImage_v80.safetensors",
|
||||
"downloadUrl": "https://civitai.com/api/download/models/3284136?fileId=3168412",
|
||||
}
|
||||
],
|
||||
}
|
||||
metadata_provider.get_version_file_mini = AsyncMock(
|
||||
return_value={"fileName": "CyberRealistic_zit_v8.0_bf16.safetensors"}
|
||||
)
|
||||
|
||||
captured = {}
|
||||
|
||||
async def fake_execute_download(self, **kwargs):
|
||||
captured["download_urls"] = kwargs["download_urls"]
|
||||
captured["file_path"] = kwargs["metadata"].file_path
|
||||
return {"success": True}
|
||||
|
||||
monkeypatch.setattr(
|
||||
DownloadManager, "_execute_download", fake_execute_download, raising=False
|
||||
)
|
||||
|
||||
result = await manager.download_from_civitai(
|
||||
model_version_id=3284136,
|
||||
save_dir=str(tmp_path),
|
||||
use_default_paths=True,
|
||||
progress_callback=None,
|
||||
source=None,
|
||||
)
|
||||
|
||||
assert result["success"] is True, result
|
||||
metadata_provider.get_version_file_mini.assert_awaited_once_with(3284136, 3168412)
|
||||
assert captured["file_path"].endswith("CyberRealistic_zit_v8.0_bf16.safetensors")
|
||||
# The file's own pinned downloadUrl is untouched.
|
||||
assert captured["download_urls"] == [
|
||||
"https://civitai.com/api/download/models/3284136?fileId=3168412"
|
||||
]
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_download_falls_back_to_rest_name_when_mini_fails(
|
||||
monkeypatch, scanners, metadata_provider, tmp_path
|
||||
):
|
||||
"""A failed/absent mini lookup must keep the previous behavior."""
|
||||
manager = DownloadManager()
|
||||
metadata_provider.payload = {
|
||||
"id": 42,
|
||||
"model": {"type": "Checkpoint", "tags": ["fantasy"]},
|
||||
"baseModel": "BaseModel",
|
||||
"creator": {"username": "Author"},
|
||||
"files": [
|
||||
{
|
||||
"id": 1001,
|
||||
"type": "Model",
|
||||
"primary": True,
|
||||
"name": "rewritten_v10.safetensors",
|
||||
"downloadUrl": "https://example.invalid/file.safetensors",
|
||||
}
|
||||
],
|
||||
}
|
||||
metadata_provider.get_version_file_mini = AsyncMock(return_value=None)
|
||||
|
||||
captured = {}
|
||||
|
||||
async def fake_execute_download(self, **kwargs):
|
||||
captured["file_path"] = kwargs["metadata"].file_path
|
||||
return {"success": True}
|
||||
|
||||
monkeypatch.setattr(
|
||||
DownloadManager, "_execute_download", fake_execute_download, raising=False
|
||||
)
|
||||
|
||||
result = await manager.download_from_civitai(
|
||||
model_version_id=42,
|
||||
save_dir=str(tmp_path),
|
||||
use_default_paths=True,
|
||||
progress_callback=None,
|
||||
source=None,
|
||||
)
|
||||
|
||||
assert result["success"] is True
|
||||
assert captured["file_path"].endswith("rewritten_v10.safetensors")
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_download_skips_mini_lookup_for_civarchive_source(
|
||||
monkeypatch, scanners, metadata_provider, tmp_path
|
||||
):
|
||||
"""CivArchive already serves raw stored names — no mini call."""
|
||||
manager = DownloadManager()
|
||||
mini_mock = AsyncMock(return_value={"fileName": "should_not_be_used.safetensors"})
|
||||
metadata_provider.get_version_file_mini = mini_mock
|
||||
|
||||
monkeypatch.setattr(
|
||||
download_manager,
|
||||
"get_metadata_provider",
|
||||
AsyncMock(return_value=metadata_provider),
|
||||
)
|
||||
|
||||
captured = {}
|
||||
|
||||
async def fake_execute_download(self, **kwargs):
|
||||
captured["file_path"] = kwargs["metadata"].file_path
|
||||
return {"success": True}
|
||||
|
||||
monkeypatch.setattr(
|
||||
DownloadManager, "_execute_download", fake_execute_download, raising=False
|
||||
)
|
||||
|
||||
result = await manager.download_from_civitai(
|
||||
model_version_id=99,
|
||||
save_dir=str(tmp_path),
|
||||
use_default_paths=True,
|
||||
progress_callback=None,
|
||||
source="civarchive",
|
||||
)
|
||||
|
||||
assert result["success"] is True
|
||||
mini_mock.assert_not_called()
|
||||
assert captured["file_path"].endswith("file.safetensors")
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_fetch_raw_file_name_edge_cases():
|
||||
"""_fetch_raw_file_name never raises and strips path components."""
|
||||
manager = DownloadManager()
|
||||
|
||||
provider = SimpleNamespace()
|
||||
|
||||
# Missing version id / file id short-circuit before any provider call.
|
||||
provider.get_version_file_mini = AsyncMock()
|
||||
assert await manager._fetch_raw_file_name(provider, None, 1) is None
|
||||
assert await manager._fetch_raw_file_name(provider, 1, None) is None
|
||||
provider.get_version_file_mini.assert_not_called()
|
||||
|
||||
# Provider without the method (older mocks / non-CivitAI providers).
|
||||
assert await manager._fetch_raw_file_name(object(), 1, 2) is None
|
||||
|
||||
# Non-dict payload, empty fileName.
|
||||
provider.get_version_file_mini = AsyncMock(return_value="oops")
|
||||
assert await manager._fetch_raw_file_name(provider, 1, 2) is None
|
||||
provider.get_version_file_mini = AsyncMock(return_value={"fileName": " "})
|
||||
assert await manager._fetch_raw_file_name(provider, 1, 2) is None
|
||||
|
||||
# Path components are stripped defensively.
|
||||
provider.get_version_file_mini = AsyncMock(
|
||||
return_value={"fileName": "../evil/model.safetensors"}
|
||||
)
|
||||
assert await manager._fetch_raw_file_name(provider, 1, 2) == "model.safetensors"
|
||||
|
||||
# Provider exceptions degrade to None.
|
||||
provider.get_version_file_mini = AsyncMock(side_effect=RuntimeError("boom"))
|
||||
assert await manager._fetch_raw_file_name(provider, 1, 2) is None
|
||||
|
||||
@@ -8,8 +8,9 @@ from unittest import mock
|
||||
|
||||
import pytest
|
||||
|
||||
from py.services.llm_service import LLMService
|
||||
from py.services import llm_service as llm_module
|
||||
from py.services.errors import LLMNotConfiguredError, LLMRateLimitError, LLMResponseError
|
||||
from py.services.llm_service import LLMService, fetch_ollama_models
|
||||
|
||||
|
||||
class MockSettings:
|
||||
@@ -314,3 +315,61 @@ class TestLLMServiceChatCompletionJson:
|
||||
system_prompt="test",
|
||||
user_prompt="test",
|
||||
)
|
||||
|
||||
|
||||
class MockGetSession:
|
||||
"""Minimal aiohttp session mock supporting get() for catalog tests."""
|
||||
|
||||
def __init__(self, response):
|
||||
self._response = response
|
||||
|
||||
def get(self, url):
|
||||
return self._response
|
||||
|
||||
async def __aenter__(self):
|
||||
return self
|
||||
|
||||
async def __aexit__(self, *args):
|
||||
pass
|
||||
|
||||
|
||||
class CorruptJsonResponse(MockResponse):
|
||||
"""Response whose body cannot be decoded as UTF-8 (like the issue's 0x9a byte)."""
|
||||
|
||||
async def json(self):
|
||||
raise UnicodeDecodeError("utf-8", b"\x9a", 0, 1, "invalid start byte")
|
||||
|
||||
|
||||
class TestModelCatalog:
|
||||
"""Tests for _load_model_catalog / fetch_ollama_models error handling."""
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _reset_catalog_cache(self):
|
||||
"""Reset the module-level catalog cache around each test."""
|
||||
llm_module._catalog_cache = None
|
||||
llm_module._model_output_limits = {}
|
||||
yield
|
||||
llm_module._catalog_cache = None
|
||||
llm_module._model_output_limits = {}
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_load_model_catalog_falls_back_on_unicode_decode_error(self):
|
||||
"""Corrupted catalog body must not raise — fall back to an empty dict."""
|
||||
response = CorruptJsonResponse(200)
|
||||
session = MockGetSession(response)
|
||||
|
||||
with mock.patch("aiohttp.ClientSession", return_value=session):
|
||||
catalog = await llm_module._load_model_catalog()
|
||||
|
||||
assert catalog == {}
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_fetch_ollama_models_falls_back_on_unicode_decode_error(self):
|
||||
"""Corrupted Ollama response must not raise — fall back to an empty list."""
|
||||
response = CorruptJsonResponse(200)
|
||||
session = MockGetSession(response)
|
||||
|
||||
with mock.patch("aiohttp.ClientSession", return_value=session):
|
||||
models = await fetch_ollama_models("http://localhost:11434/v1")
|
||||
|
||||
assert models == []
|
||||
|
||||
@@ -207,3 +207,62 @@ async def test_retry_helper_retries_normally_for_small_retry_after(monkeypatch):
|
||||
result, _ = await helper.run("test", succeeding)
|
||||
assert result == {"ok": True}
|
||||
assert calls == 2 # Retried once (small retry_after)
|
||||
|
||||
|
||||
class MiniCapableProvider(ModelMetadataProvider):
|
||||
"""Provider that serves raw file names via the mini endpoint (#1100)."""
|
||||
|
||||
def __init__(self, payload=None) -> None:
|
||||
self.payload = payload
|
||||
self.calls = []
|
||||
|
||||
async def get_model_by_hash(self, model_hash: str):
|
||||
return None, None
|
||||
|
||||
async def get_model_versions(self, model_id: str):
|
||||
return None
|
||||
|
||||
async def get_model_version(self, model_id=None, version_id=None):
|
||||
return None
|
||||
|
||||
async def get_model_version_info(self, version_id: str):
|
||||
return None, None
|
||||
|
||||
async def get_user_models(self, username: str, cursor=None):
|
||||
return None
|
||||
|
||||
async def get_version_file_mini(self, version_id: int, file_id: int):
|
||||
self.calls.append((version_id, file_id))
|
||||
return self.payload
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_base_provider_get_version_file_mini_defaults_to_none():
|
||||
provider = TrackingProvider()
|
||||
assert await provider.get_version_file_mini(1, 2) is None
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_fallback_get_version_file_mini_returns_first_hit():
|
||||
primary = TrackingProvider() # base default: None
|
||||
secondary = MiniCapableProvider({"fileName": "raw.safetensors"})
|
||||
|
||||
fallback = FallbackMetadataProvider(
|
||||
[("primary", primary), ("secondary", secondary)],
|
||||
)
|
||||
|
||||
result = await fallback.get_version_file_mini(10, 20)
|
||||
|
||||
assert result == {"fileName": "raw.safetensors"}
|
||||
assert secondary.calls == [(10, 20)]
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_rate_limit_retrying_provider_delegates_get_version_file_mini():
|
||||
inner = MiniCapableProvider({"fileName": "raw.safetensors"})
|
||||
wrapper = RateLimitRetryingProvider(inner, label="inner")
|
||||
|
||||
result = await wrapper.get_version_file_mini(10, 20)
|
||||
|
||||
assert result == {"fileName": "raw.safetensors"}
|
||||
assert inner.calls == [(10, 20)]
|
||||
|
||||
@@ -1,327 +0,0 @@
|
||||
import pytest
|
||||
import asyncio
|
||||
from typing import Any, Dict
|
||||
from unittest.mock import AsyncMock, MagicMock
|
||||
from py.services.recipe_scanner import RecipeScanner
|
||||
from types import SimpleNamespace
|
||||
|
||||
# We define these here to help with spec= if needed
|
||||
class MockCivitaiClient:
|
||||
async def get_image_info(self, image_id, source_url=None):
|
||||
pass
|
||||
|
||||
class MockPersistenceService:
|
||||
async def save_recipe(self, recipe):
|
||||
pass
|
||||
|
||||
@pytest.fixture
|
||||
def mock_civitai_client():
|
||||
client = MagicMock(spec=MockCivitaiClient)
|
||||
client.get_image_info = AsyncMock()
|
||||
return client
|
||||
|
||||
@pytest.fixture
|
||||
def mock_metadata_provider():
|
||||
provider = MagicMock()
|
||||
provider.get_model_version_info = AsyncMock(return_value=(None, None))
|
||||
provider.get_model_by_hash = AsyncMock(return_value=(None, None))
|
||||
return provider
|
||||
|
||||
@pytest.fixture
|
||||
def recipe_scanner():
|
||||
lora_scanner = MagicMock()
|
||||
lora_scanner.get_cached_data = AsyncMock(return_value=SimpleNamespace(raw_data=[]))
|
||||
|
||||
scanner = RecipeScanner(lora_scanner=lora_scanner)
|
||||
return scanner
|
||||
|
||||
@pytest.fixture
|
||||
def setup_scanner(recipe_scanner, mock_civitai_client, mock_metadata_provider, monkeypatch):
|
||||
monkeypatch.setattr(recipe_scanner, "_get_civitai_client", AsyncMock(return_value=mock_civitai_client))
|
||||
|
||||
# Wrap the real method with a mock so we can check calls but still execute it
|
||||
real_save = recipe_scanner._save_recipe_persistently
|
||||
mock_save = AsyncMock(side_effect=real_save)
|
||||
monkeypatch.setattr(recipe_scanner, "_save_recipe_persistently", mock_save)
|
||||
|
||||
monkeypatch.setattr("py.recipes.enrichment.get_default_metadata_provider", AsyncMock(return_value=mock_metadata_provider))
|
||||
|
||||
# Mock get_recipe_json_path to avoid file system issues in tests
|
||||
recipe_scanner.get_recipe_json_path = AsyncMock(return_value="/tmp/test_recipe.json")
|
||||
# Mock open to avoid actual file writing
|
||||
monkeypatch.setattr("builtins.open", MagicMock())
|
||||
monkeypatch.setattr("json.dump", MagicMock())
|
||||
monkeypatch.setattr("os.path.exists", MagicMock(return_value=False)) # avoid EXIF logic
|
||||
|
||||
return recipe_scanner, mock_civitai_client, mock_metadata_provider
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_repair_all_recipes_skip_up_to_date(setup_scanner):
|
||||
recipe_scanner, _, _ = setup_scanner
|
||||
|
||||
recipe_scanner._cache = SimpleNamespace(raw_data=[
|
||||
{"id": "r1", "repair_version": RecipeScanner.REPAIR_VERSION, "title": "Up to date"}
|
||||
])
|
||||
|
||||
# Run
|
||||
results = await recipe_scanner.repair_all_recipes()
|
||||
|
||||
# Verify
|
||||
assert results["repaired"] == 0
|
||||
assert results["skipped"] == 1
|
||||
recipe_scanner._save_recipe_persistently.assert_not_called()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_repair_all_recipes_with_enriched_checkpoint_id(setup_scanner):
|
||||
recipe_scanner, mock_civitai_client, mock_metadata_provider = setup_scanner
|
||||
|
||||
recipe = {
|
||||
"id": "r1",
|
||||
"title": "Old Recipe",
|
||||
"source_path": "https://civitai.com/images/12345",
|
||||
"checkpoint": None,
|
||||
"gen_params": {"prompt": ""}
|
||||
}
|
||||
recipe_scanner._cache = SimpleNamespace(raw_data=[recipe])
|
||||
|
||||
# Mock image info returning modelVersionId
|
||||
mock_civitai_client.get_image_info.return_value = {
|
||||
"modelVersionId": 5678,
|
||||
"meta": {"prompt": "a beautiful forest", "Checkpoint": "basic_name.safetensors"}
|
||||
}
|
||||
|
||||
# Mock metadata provider returning full info
|
||||
mock_metadata_provider.get_model_version_info.return_value = ({
|
||||
"id": 5678,
|
||||
"modelId": 1234,
|
||||
"name": "v1.0",
|
||||
"model": {"name": "Full Model Name", "type": "Checkpoint"},
|
||||
"baseModel": "SDXL 1.0",
|
||||
"images": [{"url": "https://image.url/thumb.jpg"}],
|
||||
"files": [{"type": "Model", "hashes": {"SHA256": "ABCDEF"}, "name": "full_filename.safetensors"}]
|
||||
}, None)
|
||||
|
||||
# Run
|
||||
results = await recipe_scanner.repair_all_recipes()
|
||||
|
||||
# Verify
|
||||
assert results["repaired"] == 1
|
||||
mock_metadata_provider.get_model_version_info.assert_called_with("5678")
|
||||
|
||||
saved_recipe = recipe_scanner._save_recipe_persistently.call_args[0][0]
|
||||
checkpoint = saved_recipe["checkpoint"]
|
||||
assert checkpoint["modelName"] == "Full Model Name"
|
||||
assert checkpoint["modelVersionName"] == "v1.0"
|
||||
assert checkpoint["modelId"] == 1234
|
||||
assert checkpoint["modelVersionId"] == 5678
|
||||
assert checkpoint["type"] == "checkpoint"
|
||||
assert "name" not in checkpoint
|
||||
assert "version" not in checkpoint
|
||||
assert "hash" not in checkpoint
|
||||
assert "file_name" not in checkpoint
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_repair_all_recipes_supports_civitai_red_source_url(setup_scanner):
|
||||
recipe_scanner, mock_civitai_client, mock_metadata_provider = setup_scanner
|
||||
|
||||
recipe = {
|
||||
"id": "r1",
|
||||
"title": "Red Recipe",
|
||||
"source_path": "https://civitai.red/images/12345",
|
||||
"checkpoint": None,
|
||||
"gen_params": {"prompt": ""},
|
||||
}
|
||||
recipe_scanner._cache = SimpleNamespace(raw_data=[recipe])
|
||||
|
||||
mock_civitai_client.get_image_info.return_value = {
|
||||
"modelVersionId": 5678,
|
||||
"meta": {"prompt": "from red"},
|
||||
}
|
||||
mock_metadata_provider.get_model_version_info.return_value = (
|
||||
{
|
||||
"id": 5678,
|
||||
"modelId": 1234,
|
||||
"name": "v1.0",
|
||||
"model": {"name": "Full Model Name", "type": "Checkpoint"},
|
||||
"baseModel": "SDXL 1.0",
|
||||
"images": [{"url": "https://image.url/thumb.jpg"}],
|
||||
"files": [
|
||||
{
|
||||
"type": "Model",
|
||||
"hashes": {"SHA256": "ABCDEF"},
|
||||
"name": "full_filename.safetensors",
|
||||
}
|
||||
],
|
||||
},
|
||||
None,
|
||||
)
|
||||
|
||||
results = await recipe_scanner.repair_all_recipes()
|
||||
|
||||
assert results["repaired"] == 1
|
||||
mock_civitai_client.get_image_info.assert_called_with(
|
||||
"12345", source_url="https://civitai.red/images/12345"
|
||||
)
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_repair_all_recipes_with_enriched_checkpoint_hash(setup_scanner):
|
||||
recipe_scanner, mock_civitai_client, mock_metadata_provider = setup_scanner
|
||||
|
||||
recipe = {
|
||||
"id": "r1",
|
||||
"title": "Embedded Only",
|
||||
"checkpoint": None,
|
||||
"gen_params": {
|
||||
"prompt": "",
|
||||
"Model hash": "hash123"
|
||||
}
|
||||
}
|
||||
recipe_scanner._cache = SimpleNamespace(raw_data=[recipe])
|
||||
|
||||
# Mock metadata provider lookup by hash
|
||||
mock_metadata_provider.get_model_by_hash.return_value = ({
|
||||
"id": 999,
|
||||
"modelId": 888,
|
||||
"name": "v2.0",
|
||||
"model": {"name": "Hashed Model", "type": "Checkpoint"},
|
||||
"baseModel": "SD 1.5",
|
||||
"files": [{"type": "Model", "hashes": {"SHA256": "hash123"}, "name": "hashed.safetensors"}]
|
||||
}, None)
|
||||
|
||||
# Run
|
||||
results = await recipe_scanner.repair_all_recipes()
|
||||
|
||||
# Verify
|
||||
assert results["repaired"] == 1
|
||||
mock_metadata_provider.get_model_by_hash.assert_called_with("hash123")
|
||||
|
||||
saved_recipe = recipe_scanner._save_recipe_persistently.call_args[0][0]
|
||||
checkpoint = saved_recipe["checkpoint"]
|
||||
assert checkpoint["modelName"] == "Hashed Model"
|
||||
assert checkpoint["modelVersionName"] == "v2.0"
|
||||
assert checkpoint["modelId"] == 888
|
||||
assert checkpoint["type"] == "checkpoint"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_repair_all_recipes_fallback_to_basic(setup_scanner):
|
||||
recipe_scanner, mock_civitai_client, mock_metadata_provider = setup_scanner
|
||||
|
||||
recipe = {
|
||||
"id": "r1",
|
||||
"title": "No Meta Lookup",
|
||||
"checkpoint": None,
|
||||
"gen_params": {
|
||||
"prompt": "",
|
||||
"Checkpoint": "just_a_name.safetensors"
|
||||
}
|
||||
}
|
||||
recipe_scanner._cache = SimpleNamespace(raw_data=[recipe])
|
||||
|
||||
# Mock metadata provider returning nothing
|
||||
mock_metadata_provider.get_model_by_hash.return_value = (None, "Model not found")
|
||||
|
||||
# Run
|
||||
results = await recipe_scanner.repair_all_recipes()
|
||||
|
||||
# Verify
|
||||
assert results["repaired"] == 1
|
||||
saved_recipe = recipe_scanner._save_recipe_persistently.call_args[0][0]
|
||||
assert saved_recipe["checkpoint"]["modelName"] == "just_a_name.safetensors"
|
||||
assert saved_recipe["checkpoint"]["type"] == "checkpoint"
|
||||
assert "modelId" not in saved_recipe["checkpoint"]
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_repair_all_recipes_progress_callback(setup_scanner):
|
||||
recipe_scanner, _, _ = setup_scanner
|
||||
|
||||
recipe_scanner._cache = SimpleNamespace(raw_data=[
|
||||
{"id": "r1", "title": "R1", "checkpoint": None},
|
||||
{"id": "r2", "title": "R2", "checkpoint": None}
|
||||
])
|
||||
|
||||
progress_calls = []
|
||||
async def progress_callback(data):
|
||||
progress_calls.append(data)
|
||||
|
||||
# Run
|
||||
await recipe_scanner.repair_all_recipes(
|
||||
progress_callback=progress_callback
|
||||
)
|
||||
|
||||
# Verify
|
||||
assert len(progress_calls) >= 2
|
||||
assert progress_calls[-1]["status"] == "completed"
|
||||
assert progress_calls[-1]["total"] == 2
|
||||
assert progress_calls[-1]["repaired"] == 2
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_repair_all_recipes_strips_runtime_fields(setup_scanner):
|
||||
recipe_scanner, mock_civitai_client, mock_metadata_provider = setup_scanner
|
||||
|
||||
# Recipe with runtime fields
|
||||
recipe: Dict[str, Any] = {
|
||||
"id": "r1",
|
||||
"title": "Cleanup Test",
|
||||
"checkpoint": {
|
||||
"name": "CP",
|
||||
"inLibrary": True,
|
||||
"localPath": "/path/to/cp",
|
||||
"thumbnailUrl": "thumb.jpg"
|
||||
},
|
||||
"loras": [
|
||||
{
|
||||
"name": "L1",
|
||||
"weight": 0.8,
|
||||
"inLibrary": True,
|
||||
"localPath": "/path/to/l1",
|
||||
"preview_url": "p.jpg"
|
||||
}
|
||||
],
|
||||
"gen_params": {"prompt": ""}
|
||||
}
|
||||
recipe_scanner._cache = SimpleNamespace(raw_data=[recipe])
|
||||
# Set high version to trigger repair if needed (or just ensure it processes)
|
||||
recipe["repair_version"] = 0
|
||||
|
||||
# Run
|
||||
await recipe_scanner.repair_all_recipes()
|
||||
|
||||
# Verify sanitation
|
||||
assert recipe_scanner._save_recipe_persistently.called
|
||||
saved_recipe = recipe_scanner._save_recipe_persistently.call_args[0][0]
|
||||
|
||||
# 1. Check LORA
|
||||
lora = saved_recipe["loras"][0]
|
||||
assert "inLibrary" not in lora
|
||||
assert "localPath" not in lora
|
||||
assert "preview_url" not in lora
|
||||
assert "strength" in lora # weight renamed to strength
|
||||
assert lora["strength"] == 0.8
|
||||
|
||||
# 2. Check Checkpoint
|
||||
cp = saved_recipe["checkpoint"]
|
||||
assert "inLibrary" not in cp
|
||||
assert "localPath" not in cp
|
||||
assert "thumbnailUrl" not in cp
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_sanitize_recipe_for_storage(recipe_scanner):
|
||||
|
||||
recipe = {
|
||||
"loras": [{"name": "L1", "inLibrary": True, "weight": 0.5}],
|
||||
"checkpoint": {"name": "CP", "localPath": "/tmp/cp"}
|
||||
}
|
||||
|
||||
clean = recipe_scanner._sanitize_recipe_for_storage(recipe)
|
||||
|
||||
assert "inLibrary" not in clean["loras"][0]
|
||||
assert "strength" in clean["loras"][0]
|
||||
assert clean["loras"][0]["strength"] == 0.5
|
||||
assert "localPath" not in clean["checkpoint"]
|
||||
# Testing based on what enricher would produce if it ran,
|
||||
# but here we are just testing the sanitizer which handles what is ALREADY there.
|
||||
# However, the sanitizer doesn't rename fields, it just removes runtime ones.
|
||||
# Since we changed the enricher to NOT put 'name' anymore, this test case
|
||||
# should probably reflect the new fields if it's simulating a real recipe.
|
||||
assert clean["checkpoint"]["name"] == "CP"
|
||||
@@ -242,22 +242,14 @@ async def test_is_recipe_rematch_running_by_status(manager, status, expected):
|
||||
assert manager.is_recipe_rematch_running() is expected
|
||||
|
||||
|
||||
async def test_rematch_and_repair_channels_are_independent(manager):
|
||||
# Rematch progress must not leak into the repair channel
|
||||
async def test_rematch_progress_channel_updates_and_cleans_up(manager):
|
||||
# Rematch progress is stored and reported as running while processing.
|
||||
await manager.broadcast_recipe_rematch_progress({"status": "processing", "current": 1})
|
||||
assert manager.is_recipe_rematch_running() is True
|
||||
assert manager.is_recipe_repair_running() is False
|
||||
assert manager.get_recipe_repair_progress() is None
|
||||
|
||||
# Repair progress must not overwrite the rematch state
|
||||
await manager.broadcast_recipe_repair_progress({"status": "processing", "current": 1})
|
||||
assert manager.is_recipe_repair_running() is True
|
||||
assert manager.is_recipe_rematch_running() is True
|
||||
assert manager.get_recipe_rematch_progress() == {"status": "processing", "current": 1}
|
||||
|
||||
# Cleaning the rematch channel must leave the repair channel untouched
|
||||
# Finished states clear on cleanup.
|
||||
await manager.broadcast_recipe_rematch_progress({"status": "completed"})
|
||||
manager.cleanup_recipe_rematch_progress()
|
||||
assert manager.get_recipe_rematch_progress() is None
|
||||
assert manager.get_recipe_repair_progress() == {"status": "processing", "current": 1}
|
||||
assert manager.is_recipe_repair_running() is True
|
||||
assert manager.is_recipe_rematch_running() is False
|
||||
|
||||
@@ -40,7 +40,6 @@ def sample_recipes() -> List[Dict[str, Any]]:
|
||||
"created_date": 1700000000.0,
|
||||
"modified": 1700000100.0,
|
||||
"favorite": True,
|
||||
"repair_version": 3,
|
||||
"preview_nsfw_level": 1,
|
||||
"loras": [
|
||||
{"hash": "hash1", "file_name": "lora1", "strength": 0.8},
|
||||
@@ -60,7 +59,6 @@ def sample_recipes() -> List[Dict[str, Any]]:
|
||||
"created_date": 1700000200.0,
|
||||
"modified": 1700000300.0,
|
||||
"favorite": False,
|
||||
"repair_version": 2,
|
||||
"preview_nsfw_level": 0,
|
||||
"loras": [{"hash": "hash3", "file_name": "lora3", "strength": 0.5}],
|
||||
"gen_params": {"prompt": "another prompt"},
|
||||
@@ -101,7 +99,6 @@ class TestPersistentRecipeCache:
|
||||
assert r1["base_model"] == "SD1.5"
|
||||
assert r1["fingerprint"] == "abc123"
|
||||
assert r1["favorite"] is True
|
||||
assert r1["repair_version"] == 3
|
||||
assert len(r1["loras"]) == 2
|
||||
assert r1["loras"][0]["hash"] == "hash1"
|
||||
assert r1["checkpoint"]["name"] == "model.safetensors"
|
||||
@@ -164,7 +161,6 @@ class TestPersistentRecipeCache:
|
||||
file_mtime REAL,
|
||||
file_size INTEGER,
|
||||
favorite INTEGER DEFAULT 0,
|
||||
repair_version INTEGER DEFAULT 0,
|
||||
preview_nsfw_level INTEGER DEFAULT 0,
|
||||
loras_json TEXT,
|
||||
checkpoint_json TEXT,
|
||||
@@ -710,7 +706,6 @@ class TestHasWorkflowColumn:
|
||||
file_mtime REAL,
|
||||
file_size INTEGER,
|
||||
favorite INTEGER DEFAULT 0,
|
||||
repair_version INTEGER DEFAULT 0,
|
||||
preview_nsfw_level INTEGER DEFAULT 0,
|
||||
loras_json TEXT,
|
||||
checkpoint_json TEXT,
|
||||
|
||||
Reference in New Issue
Block a user